Search Results for author: Dong Li

Found 124 papers, 29 papers with code

ProgressFace: Scale-Aware Progressive Learning for Face Detection

no code implementations ECCV 2020 Jiashu Zhu, Dong Li, Tiantian Han, Lu Tian, Yi Shan

In this work, we propose a novel scale-aware progressive training mechanism to address large scale variations across faces.

Face Detection

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

no code implementations8 Mar 2024 Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-Baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, Ioannis Antonoglou, Rohan Anil, Sebastian Borgeaud, Andrew Dai, Katie Millican, Ethan Dyer, Mia Glaese, Thibault Sottiaux, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, James Molloy, Jilin Chen, Michael Isard, Paul Barham, Tom Hennigan, Ross Mcilroy, Melvin Johnson, Johan Schalkwyk, Eli Collins, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, Clemens Meyer, Gregory Thornton, Zhen Yang, Henryk Michalewski, Zaheer Abbas, Nathan Schucher, Ankesh Anand, Richard Ives, James Keeling, Karel Lenc, Salem Haykal, Siamak Shakeri, Pranav Shyam, Aakanksha Chowdhery, Roman Ring, Stephen Spencer, Eren Sezener, Luke Vilnis, Oscar Chang, Nobuyuki Morioka, George Tucker, Ce Zheng, Oliver Woodman, Nithya Attaluri, Tomas Kocisky, Evgenii Eltyshev, Xi Chen, Timothy Chung, Vittorio Selo, Siddhartha Brahma, Petko Georgiev, Ambrose Slone, Zhenkai Zhu, James Lottes, Siyuan Qiao, Ben Caine, Sebastian Riedel, Alex Tomala, Martin Chadwick, Juliette Love, Peter Choy, Sid Mittal, Neil Houlsby, Yunhao Tang, Matthew Lamm, Libin Bai, Qiao Zhang, Luheng He, Yong Cheng, Peter Humphreys, Yujia Li, Sergey Brin, Albin Cassirer, Yingjie Miao, Lukas Zilka, Taylor Tobin, Kelvin Xu, Lev Proleev, Daniel Sohn, Alberto Magni, Lisa Anne Hendricks, Isabel Gao, Santiago Ontañón, Oskar Bunyan, Nathan Byrd, Abhanshu Sharma, Biao Zhang, Mario Pinto, Rishika Sinha, Harsh Mehta, Dawei Jia, Sergi Caelles, Albert Webson, Alex Morris, Becca Roelofs, Yifan Ding, Robin Strudel, Xuehan Xiong, Marvin Ritter, Mostafa Dehghani, Rahma Chaabouni, Abhijit Karmarkar, Guangda Lai, Fabian Mentzer, Bibo Xu, Yaguang Li, Yujing Zhang, Tom Le Paine, Alex Goldin, Behnam Neyshabur, Kate Baumli, Anselm Levskaya, Michael Laskin, Wenhao Jia, Jack W. Rae, Kefan Xiao, Antoine He, Skye Giordano, Lakshman Yagati, Jean-Baptiste Lespiau, Paul Natsev, Sanjay Ganapathy, Fangyu Liu, Danilo Martins, Nanxin Chen, Yunhan Xu, Megan Barnes, Rhys May, Arpi Vezer, Junhyuk Oh, Ken Franko, Sophie Bridgers, Ruizhe Zhao, Boxi Wu, Basil Mustafa, Sean Sechrist, Emilio Parisotto, Thanumalayan Sankaranarayana Pillai, Chris Larkin, Chenjie Gu, Christina Sorokin, Maxim Krikun, Alexey Guseynov, Jessica Landon, Romina Datta, Alexander Pritzel, Phoebe Thacker, Fan Yang, Kevin Hui, Anja Hauth, Chih-Kuan Yeh, David Barker, Justin Mao-Jones, Sophia Austin, Hannah Sheahan, Parker Schuh, James Svensson, Rohan Jain, Vinay Ramasesh, Anton Briukhov, Da-Woon Chung, Tamara von Glehn, Christina Butterfield, Priya Jhakra, Matthew Wiethoff, Justin Frye, Jordan Grimstad, Beer Changpinyo, Charline Le Lan, Anna Bortsova, Yonghui Wu, Paul Voigtlaender, Tara Sainath, Charlotte Smith, Will Hawkins, Kris Cao, James Besley, Srivatsan Srinivasan, Mark Omernick, Colin Gaffney, Gabriela Surita, Ryan Burnell, Bogdan Damoc, Junwhan Ahn, Andrew Brock, Mantas Pajarskas, Anastasia Petrushkina, Seb Noury, Lorenzo Blanco, Kevin Swersky, Arun Ahuja, Thi Avrahami, Vedant Misra, Raoul de Liedekerke, Mariko Iinuma, Alex Polozov, Sarah York, George van den Driessche, Paul Michel, Justin Chiu, Rory Blevins, Zach Gleicher, Adrià Recasens, Alban Rrustemi, Elena Gribovskaya, Aurko Roy, Wiktor Gworek, Séb Arnold, Lisa Lee, James Lee-Thorp, Marcello Maggioni, Enrique Piqueras, Kartikeya Badola, Sharad Vikram, Lucas Gonzalez, Anirudh Baddepudi, Evan Senter, Jacob Devlin, James Qin, Michael Azzam, Maja Trebacz, Martin Polacek, Kashyap Krishnakumar, Shuo-Yiin Chang, Matthew Tung, Ivo Penchev, Rishabh Joshi, Kate Olszewska, Carrie Muir, Mateo Wirth, Ale Jakse Hartman, Josh Newlan, Sheleem Kashem, Vijay Bolina, Elahe Dabir, Joost van Amersfoort, Zafarali Ahmed, James Cobon-Kerr, Aishwarya Kamath, Arnar Mar Hrafnkelsson, Le Hou, Ian Mackinnon, Alexandre Frechette, Eric Noland, Xiance Si, Emanuel Taropa, Dong Li, Phil Crone, Anmol Gulati, Sébastien Cevey, Jonas Adler, Ada Ma, David Silver, Simon Tokumine, Richard Powell, Stephan Lee, Michael Chang, Samer Hassan, Diana Mincu, Antoine Yang, Nir Levine, Jenny Brennan, Mingqiu Wang, Sarah Hodkinson, Jeffrey Zhao, Josh Lipschultz, Aedan Pope, Michael B. Chang, Cheng Li, Laurent El Shafey, Michela Paganini, Sholto Douglas, Bernd Bohnet, Fabio Pardo, Seth Odoom, Mihaela Rosca, Cicero Nogueira dos santos, Kedar Soparkar, Arthur Guez, Tom Hudson, Steven Hansen, Chulayuth Asawaroengchai, Ravi Addanki, Tianhe Yu, Wojciech Stokowiec, Mina Khan, Justin Gilmer, Jaehoon Lee, Carrie Grimes Bostock, Keran Rong, Jonathan Caton, Pedram Pejman, Filip Pavetic, Geoff Brown, Vivek Sharma, Mario Lučić, Rajkumar Samuel, Josip Djolonga, Amol Mandhane, Lars Lowe Sjösund, Elena Buchatskaya, Elspeth White, Natalie Clay, Jiepu Jiang, Hyeontaek Lim, Ross Hemsley, Jane Labanowski, Nicola De Cao, David Steiner, Sayed Hadi Hashemi, Jacob Austin, Anita Gergely, Tim Blyth, Joe Stanton, Kaushik Shivakumar, Aditya Siddhant, Anders Andreassen, Carlos Araya, Nikhil Sethi, Rakesh Shivanna, Steven Hand, Ankur Bapna, Ali Khodaei, Antoine Miech, Garrett Tanzer, Andy Swing, Shantanu Thakoor, Zhufeng Pan, Zachary Nado, Stephanie Winkler, Dian Yu, Mohammad Saleh, Loren Maggiore, Iain Barr, Minh Giang, Thais Kagohara, Ivo Danihelka, Amit Marathe, Vladimir Feinberg, Nimesh Ghelani, Dan Horgan, Helen Miller, Lexi Walker, Richard Tanburn, Mukarram Tariq, Disha Shrivastava, Fei Xia, Chung-Cheng Chiu, Khuslen Baatarsukh, Sina Samangooei, Fred Alcober, Axel Stjerngren, Paul Komarek, Katerina Tsihlas, Anudhyan Boral, Ramona Comanescu, Jeremy Chen, Ruibo Liu, Dawn Bloxwich, Charlie Chen, Yanhua Sun, Fangxiaoyu Feng, Matthew Mauger, Xerxes Dotiwalla, Vincent Hellendoorn, Michael Sharman, Ivy Zheng, Krishna Haridasan, Gabe Barth-Maron, Craig Swanson, Dominika Rogozińska, Alek Andreev, Paul Kishan Rubenstein, Ruoxin Sang, Dan Hurt, Gamaleldin Elsayed, Renshen Wang, Dave Lacey, Anastasija Ilić, Yao Zhao, Lora Aroyo, Chimezie Iwuanyanwu, Vitaly Nikolaev, Balaji Lakshminarayanan, Sadegh Jazayeri, Raphaël Lopez Kaufman, Mani Varadarajan, Chetan Tekur, Doug Fritz, Misha Khalman, David Reitter, Kingshuk Dasgupta, Shourya Sarcar, Tina Ornduff, Javier Snaider, Fantine Huot, Johnson Jia, Rupert Kemp, Nejc Trdin, Anitha Vijayakumar, Lucy Kim, Christof Angermueller, Li Lao, Tianqi Liu, Haibin Zhang, David Engel, Somer Greene, Anaïs White, Jessica Austin, Lilly Taylor, Shereen Ashraf, Dangyi Liu, Maria Georgaki, Irene Cai, Yana Kulizhskaya, Sonam Goenka, Brennan Saeta, Kiran Vodrahalli, Christian Frank, Dario de Cesare, Brona Robenek, Harry Richardson, Mahmoud Alnahlawi, Christopher Yew, Priya Ponnapalli, Marco Tagliasacchi, Alex Korchemniy, Yelin Kim, Dinghua Li, Bill Rosgen, Zoe Ashwood, Kyle Levin, Jeremy Wiesner, Praseem Banzal, Praveen Srinivasan, Hongkun Yu, Çağlar Ünlü, David Reid, Zora Tung, Daniel Finchelstein, Ravin Kumar, Andre Elisseeff, Jin Huang, Ming Zhang, Rui Zhu, Ricardo Aguilar, Mai Giménez, Jiawei Xia, Olivier Dousse, Willi Gierke, Soheil Hassas Yeganeh, Damion Yates, Komal Jalan, Lu Li, Eri Latorre-Chimoto, Duc Dung Nguyen, Ken Durden, Praveen Kallakuri, Yaxin Liu, Matthew Johnson, Tomy Tsai, Alice Talbert, Jasmine Liu, Alexander Neitz, Chen Elkind, Marco Selvi, Mimi Jasarevic, Livio Baldini Soares, Albert Cui, Pidong Wang, Alek Wenjiao Wang, Xinyu Ye, Krystal Kallarackal, Lucia Loher, Hoi Lam, Josef Broder, Dan Holtmann-Rice, Nina Martin, Bramandia Ramadhana, Daniel Toyama, Mrinal Shukla, Sujoy Basu, Abhi Mohan, Nick Fernando, Noah Fiedel, Kim Paterson, Hui Li, Ankush Garg, Jane Park, DongHyun Choi, Diane Wu, Sankalp Singh, Zhishuai Zhang, Amir Globerson, Lily Yu, John Carpenter, Félix de Chaumont Quitry, Carey Radebaugh, Chu-Cheng Lin, Alex Tudor, Prakash Shroff, Drew Garmon, Dayou Du, Neera Vats, Han Lu, Shariq Iqbal, Alex Yakubovich, Nilesh Tripuraneni, James Manyika, Haroon Qureshi, Nan Hua, Christel Ngani, Maria Abi Raad, Hannah Forbes, Anna Bulanova, Jeff Stanway, Mukund Sundararajan, Victor Ungureanu, Colton Bishop, Yunjie Li, Balaji Venkatraman, Bo Li, Chloe Thornton, Salvatore Scellato, Nishesh Gupta, Yicheng Wang, Ian Tenney, Xihui Wu, Ashish Shenoy, Gabriel Carvajal, Diana Gage Wright, Ben Bariach, Zhuyun Xiao, Peter Hawkins, Sid Dalmia, Clement Farabet, Pedro Valenzuela, Quan Yuan, Chris Welty, Ananth Agarwal, Mia Chen, Wooyeol Kim, Brice Hulse, Nandita Dukkipati, Adam Paszke, Andrew Bolt, Elnaz Davoodi, Kiam Choo, Jennifer Beattie, Jennifer Prendki, Harsha Vashisht, Rebeca Santamaria-Fernandez, Luis C. Cobo, Jarek Wilkiewicz, David Madras, Ali Elqursh, Grant Uy, Kevin Ramirez, Matt Harvey, Tyler Liechty, Heiga Zen, Jeff Seibert, Clara Huiyi Hu, Mohamed Elhawaty, Andrey Khorlin, Maigo Le, Asaf Aharoni, Megan Li, Lily Wang, Sandeep Kumar, Alejandro Lince, Norman Casagrande, Jay Hoover, Dalia El Badawy, David Soergel, Denis Vnukov, Matt Miecnikowski, Jiri Simsa, Anna Koop, Praveen Kumar, Thibault Sellam, Daniel Vlasic, Samira Daruki, Nir Shabat, John Zhang, Guolong Su, Jiageng Zhang, Jeremiah Liu, Yi Sun, Evan Palmer, Alireza Ghaffarkhah, Xi Xiong, Victor Cotruta, Michael Fink, Lucas Dixon, Ashwin Sreevatsa, Adrian Goedeckemeyer, Alek Dimitriev, Mohsen Jafari, Remi Crocker, Nicholas FitzGerald, Aviral Kumar, Sanjay Ghemawat, Ivan Philips, Frederick Liu, Yannie Liang, Rachel Sterneck, Alena Repina, Marcus Wu, Laura Knight, Marin Georgiev, Hyo Lee, Harry Askham, Abhishek Chakladar, Annie Louis, Carl Crous, Hardie Cate, Dessie Petrova, MICHAEL QUINN, Denese Owusu-Afriyie, Achintya Singhal, Nan Wei, Solomon Kim, Damien Vincent, Milad Nasr, Christopher A. Choquette-Choo, Reiko Tojo, Shawn Lu, Diego de Las Casas, Yuchung Cheng, Tolga Bolukbasi, Katherine Lee, Saaber Fatehi, Rajagopal Ananthanarayanan, Miteyan Patel, Charbel Kaed, Jing Li, Jakub Sygnowski, Shreyas Rammohan Belle, Zhe Chen, Jaclyn Konzelmann, Siim Põder, Roopal Garg, Vinod Koverkathu, Adam Brown, Chris Dyer, Rosanne Liu, Azade Nova, Jun Xu, Slav Petrov, Demis Hassabis, Koray Kavukcuoglu, Jeffrey Dean, Oriol Vinyals

In this report, we present the latest model of the Gemini family, Gemini 1. 5 Pro, a highly compute-efficient multimodal mixture-of-experts model capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio.

Code Generation Retrieval

Contrastive Augmented Graph2Graph Memory Interaction for Few Shot Continual Learning

no code implementations7 Mar 2024 Biqing Qi, Junqi Gao, Xingquan Chen, Dong Li, Jianxing Liu, Ligang Wu, BoWen Zhou

However, current EM-based methods retrieves memory globally by performing Vector-to-Vector (V2V) interaction between features corresponding to the input and prototypes stored in EM, neglecting the geometric structure of local features.

Few-Shot Class-Incremental Learning Few-Shot Learning +1

Reinforced In-Context Black-Box Optimization

1 code implementation27 Feb 2024 Lei Song, Chenxiao Gao, Ke Xue, Chenyang Wu, Dong Li, Jianye Hao, Zongzhang Zhang, Chao Qian

In this paper, we propose RIBBO, a method to reinforce-learn a BBO algorithm from offline data in an end-to-end fashion.

In-Context Learning Meta-Learning

Supervised Algorithmic Fairness in Distribution Shifts: A Survey

no code implementations2 Feb 2024 Yujie Lin, Dong Li, Chen Zhao, Xintao Wu, Qin Tian, Minglai Shao

Supervised fairness-aware machine learning under distribution shifts is an emerging field that addresses the challenge of maintaining equitable and unbiased predictions when faced with changes in data distributions from source to target domains.

Fairness

CO2: Efficient Distributed Training with Full Communication-Computation Overlap

no code implementations29 Jan 2024 Weigao Sun, Zhen Qin, Weixuan Sun, Shidi Li, Dong Li, Xuyang Shen, Yu Qiao, Yiran Zhong

CO2 is able to attain a high scalability even on extensive multi-node clusters constrained by very limited communication bandwidth.

Real-Time Systems Optimization with Black-box Constraints and Hybrid Variables

no code implementations21 Jan 2024 Sen Wang, Dong Li, Shao-Yu Huang, Xuanliang Deng, Ashrarul H. Sifat, Changhee Jung, Ryan Williams, Haibo Zeng

When optimizing real-time systems, designers often face a challenging problem where the schedulability constraints are non-convex, non-continuous, or lack an analytical form to understand their properties.

Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

2 code implementations9 Jan 2024 Zhen Qin, Weigao Sun, Dong Li, Xuyang Shen, Weixuan Sun, Yiran Zhong

With its ability to process tokens in linear computational complexities, linear attention, in theory, can handle sequences of unlimited length without sacrificing speed, i. e., maintaining a constant training speed for various sequence lengths with a fixed memory consumption.

A General and Scalable Method for Optimizing Real-Time Systems

no code implementations6 Jan 2024 Sen Wang, Dong Li, Shao-Yu Huang, Xuanliang Deng, Ashrarul H. Sifat, Changhee Jung, Ryan Williams, Haibo Zeng

In real-time systems optimization, designers often face a challenging problem posed by the non-convex and non-continuous schedulability conditions, which may even lack an analytical form to understand their properties.

PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidance

1 code implementation28 Dec 2023 Taicai Chen, Yue Duan, Dong Li, Lei Qi, Yinghuan Shi, Yang Gao

Based on this technique, we assign appropriate training weights to unlabeled data to enhance the construction of a discriminative latent space.

Bayesian Optimization Pseudo Label

Gemini: A Family of Highly Capable Multimodal Models

no code implementations The Keyword 2023 Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M. Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy Lillicrap, Angeliki Lazaridou, Orhan Firat, James Molloy, Michael Isard, Paul R. Barham, Tom Hennigan, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, Ryan Doherty, Eli Collins, Clemens Meyer, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, George Tucker, Enrique Piqueras, Maxim Krikun, Iain Barr, Nikolay Savinov, Ivo Danihelka, Becca Roelofs, Anaïs White, Anders Andreassen, Tamara von Glehn, Lakshman Yagati, Mehran Kazemi, Lucas Gonzalez, Misha Khalman, Jakub Sygnowski, Alexandre Frechette, Charlotte Smith, Laura Culp, Lev Proleev, Yi Luan, Xi Chen, James Lottes, Nathan Schucher, Federico Lebron, Alban Rrustemi, Natalie Clay, Phil Crone, Tomas Kocisky, Jeffrey Zhao, Bartek Perz, Dian Yu, Heidi Howard, Adam Bloniarz, Jack W. Rae, Han Lu, Laurent SIfre, Marcello Maggioni, Fred Alcober, Dan Garrette, Megan Barnes, Shantanu Thakoor, Jacob Austin, Gabriel Barth-Maron, William Wong, Rishabh Joshi, Rahma Chaabouni, Deeni Fatiha, Arun Ahuja, Ruibo Liu, Yunxuan Li, Sarah Cogan, Jeremy Chen, Chao Jia, Chenjie Gu, Qiao Zhang, Jordan Grimstad, Ale Jakse Hartman, Martin Chadwick, Gaurav Singh Tomar, Xavier Garcia, Evan Senter, Emanuel Taropa, Thanumalayan Sankaranarayana Pillai, Jacob Devlin, Michael Laskin, Diego de Las Casas, Dasha Valter, Connie Tao, Lorenzo Blanco, Adrià Puigdomènech Badia, David Reitter, Mianna Chen, Jenny Brennan, Clara Rivera, Sergey Brin, Shariq Iqbal, Gabriela Surita, Jane Labanowski, Abhi Rao, Stephanie Winkler, Emilio Parisotto, Yiming Gu, Kate Olszewska, Yujing Zhang, Ravi Addanki, Antoine Miech, Annie Louis, Laurent El Shafey, Denis Teplyashin, Geoff Brown, Elliot Catt, Nithya Attaluri, Jan Balaguer, Jackie Xiang, Pidong Wang, Zoe Ashwood, Anton Briukhov, Albert Webson, Sanjay Ganapathy, Smit Sanghavi, Ajay Kannan, Ming-Wei Chang, Axel Stjerngren, Josip Djolonga, Yuting Sun, Ankur Bapna, Matthew Aitchison, Pedram Pejman, Henryk Michalewski, Tianhe Yu, Cindy Wang, Juliette Love, Junwhan Ahn, Dawn Bloxwich, Kehang Han, Peter Humphreys, Thibault Sellam, James Bradbury, Varun Godbole, Sina Samangooei, Bogdan Damoc, Alex Kaskasoli, Sébastien M. R. Arnold, Vijay Vasudevan, Shubham Agrawal, Jason Riesa, Dmitry Lepikhin, Richard Tanburn, Srivatsan Srinivasan, Hyeontaek Lim, Sarah Hodkinson, Pranav Shyam, Johan Ferret, Steven Hand, Ankush Garg, Tom Le Paine, Jian Li, Yujia Li, Minh Giang, Alexander Neitz, Zaheer Abbas, Sarah York, Machel Reid, Elizabeth Cole, Aakanksha Chowdhery, Dipanjan Das, Dominika Rogozińska, Vitaly Nikolaev, Pablo Sprechmann, Zachary Nado, Lukas Zilka, Flavien Prost, Luheng He, Marianne Monteiro, Gaurav Mishra, Chris Welty, Josh Newlan, Dawei Jia, Miltiadis Allamanis, Clara Huiyi Hu, Raoul de Liedekerke, Justin Gilmer, Carl Saroufim, Shruti Rijhwani, Shaobo Hou, Disha Shrivastava, Anirudh Baddepudi, Alex Goldin, Adnan Ozturel, Albin Cassirer, Yunhan Xu, Daniel Sohn, Devendra Sachan, Reinald Kim Amplayo, Craig Swanson, Dessie Petrova, Shashi Narayan, Arthur Guez, Siddhartha Brahma, Jessica Landon, Miteyan Patel, Ruizhe Zhao, Kevin Villela, Luyu Wang, Wenhao Jia, Matthew Rahtz, Mai Giménez, Legg Yeung, Hanzhao Lin, James Keeling, Petko Georgiev, Diana Mincu, Boxi Wu, Salem Haykal, Rachel Saputro, Kiran Vodrahalli, James Qin, Zeynep Cankara, Abhanshu Sharma, Nick Fernando, Will Hawkins, Behnam Neyshabur, Solomon Kim, Adrian Hutter, Priyanka Agrawal, Alex Castro-Ros, George van den Driessche, Tao Wang, Shuo-Yiin Chang, Paul Komarek, Ross Mcilroy, Mario Lučić, Guodong Zhang, Wael Farhan, Michael Sharman, Paul Natsev, Paul Michel, Yong Cheng, Yamini Bansal, Siyuan Qiao, Kris Cao, Siamak Shakeri, Christina Butterfield, Justin Chung, Paul Kishan Rubenstein, Shivani Agrawal, Arthur Mensch, Kedar Soparkar, Karel Lenc, Timothy Chung, Aedan Pope, Loren Maggiore, Jackie Kay, Priya Jhakra, Shibo Wang, Joshua Maynez, Mary Phuong, Taylor Tobin, Andrea Tacchetti, Maja Trebacz, Kevin Robinson, Yash Katariya, Sebastian Riedel, Paige Bailey, Kefan Xiao, Nimesh Ghelani, Lora Aroyo, Ambrose Slone, Neil Houlsby, Xuehan Xiong, Zhen Yang, Elena Gribovskaya, Jonas Adler, Mateo Wirth, Lisa Lee, Music Li, Thais Kagohara, Jay Pavagadhi, Sophie Bridgers, Anna Bortsova, Sanjay Ghemawat, Zafarali Ahmed, Tianqi Liu, Richard Powell, Vijay Bolina, Mariko Iinuma, Polina Zablotskaia, James Besley, Da-Woon Chung, Timothy Dozat, Ramona Comanescu, Xiance Si, Jeremy Greer, Guolong Su, Martin Polacek, Raphaël Lopez Kaufman, Simon Tokumine, Hexiang Hu, Elena Buchatskaya, Yingjie Miao, Mohamed Elhawaty, Aditya Siddhant, Nenad Tomasev, Jinwei Xing, Christina Greer, Helen Miller, Shereen Ashraf, Aurko Roy, Zizhao Zhang, Ada Ma, Angelos Filos, Milos Besta, Rory Blevins, Ted Klimenko, Chih-Kuan Yeh, Soravit Changpinyo, Jiaqi Mu, Oscar Chang, Mantas Pajarskas, Carrie Muir, Vered Cohen, Charline Le Lan, Krishna Haridasan, Amit Marathe, Steven Hansen, Sholto Douglas, Rajkumar Samuel, Mingqiu Wang, Sophia Austin, Chang Lan, Jiepu Jiang, Justin Chiu, Jaime Alonso Lorenzo, Lars Lowe Sjösund, Sébastien Cevey, Zach Gleicher, Thi Avrahami, Anudhyan Boral, Hansa Srinivasan, Vittorio Selo, Rhys May, Konstantinos Aisopos, Léonard Hussenot, Livio Baldini Soares, Kate Baumli, Michael B. Chang, Adrià Recasens, Ben Caine, Alexander Pritzel, Filip Pavetic, Fabio Pardo, Anita Gergely, Justin Frye, Vinay Ramasesh, Dan Horgan, Kartikeya Badola, Nora Kassner, Subhrajit Roy, Ethan Dyer, Víctor Campos, Alex Tomala, Yunhao Tang, Dalia El Badawy, Elspeth White, Basil Mustafa, Oran Lang, Abhishek Jindal, Sharad Vikram, Zhitao Gong, Sergi Caelles, Ross Hemsley, Gregory Thornton, Fangxiaoyu Feng, Wojciech Stokowiec, Ce Zheng, Phoebe Thacker, Çağlar Ünlü, Zhishuai Zhang, Mohammad Saleh, James Svensson, Max Bileschi, Piyush Patil, Ankesh Anand, Roman Ring, Katerina Tsihlas, Arpi Vezer, Marco Selvi, Toby Shevlane, Mikel Rodriguez, Tom Kwiatkowski, Samira Daruki, Keran Rong, Allan Dafoe, Nicholas FitzGerald, Keren Gu-Lemberg, Mina Khan, Lisa Anne Hendricks, Marie Pellat, Vladimir Feinberg, James Cobon-Kerr, Tara Sainath, Maribeth Rauh, Sayed Hadi Hashemi, Richard Ives, Yana Hasson, Yaguang Li, Eric Noland, Yuan Cao, Nathan Byrd, Le Hou, Qingze Wang, Thibault Sottiaux, Michela Paganini, Jean-Baptiste Lespiau, Alexandre Moufarek, Samer Hassan, Kaushik Shivakumar, Joost van Amersfoort, Amol Mandhane, Pratik Joshi, Anirudh Goyal, Matthew Tung, Andrew Brock, Hannah Sheahan, Vedant Misra, Cheng Li, Nemanja Rakićević, Mostafa Dehghani, Fangyu Liu, Sid Mittal, Junhyuk Oh, Seb Noury, Eren Sezener, Fantine Huot, Matthew Lamm, Nicola De Cao, Charlie Chen, Gamaleldin Elsayed, Ed Chi, Mahdis Mahdieh, Ian Tenney, Nan Hua, Ivan Petrychenko, Patrick Kane, Dylan Scandinaro, Rishub Jain, Jonathan Uesato, Romina Datta, Adam Sadovsky, Oskar Bunyan, Dominik Rabiej, Shimu Wu, John Zhang, Gautam Vasudevan, Edouard Leurent, Mahmoud Alnahlawi, Ionut Georgescu, Nan Wei, Ivy Zheng, Betty Chan, Pam G Rabinovitch, Piotr Stanczyk, Ye Zhang, David Steiner, Subhajit Naskar, Michael Azzam, Matthew Johnson, Adam Paszke, Chung-Cheng Chiu, Jaume Sanchez Elias, Afroz Mohiuddin, Faizan Muhammad, Jin Miao, Andrew Lee, Nino Vieillard, Sahitya Potluri, Jane Park, Elnaz Davoodi, Jiageng Zhang, Jeff Stanway, Drew Garmon, Abhijit Karmarkar, Zhe Dong, Jong Lee, Aviral Kumar, Luowei Zhou, Jonathan Evens, William Isaac, Zhe Chen, Johnson Jia, Anselm Levskaya, Zhenkai Zhu, Chris Gorgolewski, Peter Grabowski, Yu Mao, Alberto Magni, Kaisheng Yao, Javier Snaider, Norman Casagrande, Paul Suganthan, Evan Palmer, Geoffrey Irving, Edward Loper, Manaal Faruqui, Isha Arkatkar, Nanxin Chen, Izhak Shafran, Michael Fink, Alfonso Castaño, Irene Giannoumis, Wooyeol Kim, Mikołaj Rybiński, Ashwin Sreevatsa, Jennifer Prendki, David Soergel, Adrian Goedeckemeyer, Willi Gierke, Mohsen Jafari, Meenu Gaba, Jeremy Wiesner, Diana Gage Wright, Yawen Wei, Harsha Vashisht, Yana Kulizhskaya, Jay Hoover, Maigo Le, Lu Li, Chimezie Iwuanyanwu, Lu Liu, Kevin Ramirez, Andrey Khorlin, Albert Cui, Tian Lin, Marin Georgiev, Marcus Wu, Ricardo Aguilar, Keith Pallo, Abhishek Chakladar, Alena Repina, Xihui Wu, Tom van der Weide, Priya Ponnapalli, Caroline Kaplan, Jiri Simsa, Shuangfeng Li, Olivier Dousse, Jeff Piper, Nathan Ie, Minnie Lui, Rama Pasumarthi, Nathan Lintz, Anitha Vijayakumar, Lam Nguyen Thiet, Daniel Andor, Pedro Valenzuela, Cosmin Paduraru, Daiyi Peng, Katherine Lee, Shuyuan Zhang, Somer Greene, Duc Dung Nguyen, Paula Kurylowicz, Sarmishta Velury, Sebastian Krause, Cassidy Hardin, Lucas Dixon, Lili Janzer, Kiam Choo, Ziqiang Feng, Biao Zhang, Achintya Singhal, Tejasi Latkar, Mingyang Zhang, Quoc Le, Elena Allica Abellan, Dayou Du, Dan McKinnon, Natasha Antropova, Tolga Bolukbasi, Orgad Keller, David Reid, Daniel Finchelstein, Maria Abi Raad, Remi Crocker, Peter Hawkins, Robert Dadashi, Colin Gaffney, Sid Lall, Ken Franko, Egor Filonov, Anna Bulanova, Rémi Leblond, Vikas Yadav, Shirley Chung, Harry Askham, Luis C. Cobo, Kelvin Xu, Felix Fischer, Jun Xu, Christina Sorokin, Chris Alberti, Chu-Cheng Lin, Colin Evans, Hao Zhou, Alek Dimitriev, Hannah Forbes, Dylan Banarse, Zora Tung, Jeremiah Liu, Mark Omernick, Colton Bishop, Chintu Kumar, Rachel Sterneck, Ryan Foley, Rohan Jain, Swaroop Mishra, Jiawei Xia, Taylor Bos, Geoffrey Cideron, Ehsan Amid, Francesco Piccinno, Xingyu Wang, Praseem Banzal, Petru Gurita, Hila Noga, Premal Shah, Daniel J. Mankowitz, Alex Polozov, Nate Kushman, Victoria Krakovna, Sasha Brown, Mohammadhossein Bateni, Dennis Duan, Vlad Firoiu, Meghana Thotakuri, Tom Natan, Anhad Mohananey, Matthieu Geist, Sidharth Mudgal, Sertan Girgin, Hui Li, Jiayu Ye, Ofir Roval, Reiko Tojo, Michael Kwong, James Lee-Thorp, Christopher Yew, Quan Yuan, Sumit Bagri, Danila Sinopalnikov, Sabela Ramos, John Mellor, Abhishek Sharma, Aliaksei Severyn, Jonathan Lai, Kathy Wu, Heng-Tze Cheng, David Miller, Nicolas Sonnerat, Denis Vnukov, Rory Greig, Jennifer Beattie, Emily Caveness, Libin Bai, Julian Eisenschlos, Alex Korchemniy, Tomy Tsai, Mimi Jasarevic, Weize Kong, Phuong Dao, Zeyu Zheng, Frederick Liu, Fan Yang, Rui Zhu, Mark Geller, Tian Huey Teh, Jason Sanmiya, Evgeny Gladchenko, Nejc Trdin, Andrei Sozanschi, Daniel Toyama, Evan Rosen, Sasan Tavakkol, Linting Xue, Chen Elkind, Oliver Woodman, John Carpenter, George Papamakarios, Rupert Kemp, Sushant Kafle, Tanya Grunina, Rishika Sinha, Alice Talbert, Abhimanyu Goyal, Diane Wu, Denese Owusu-Afriyie, Cosmo Du, Chloe Thornton, Jordi Pont-Tuset, Pradyumna Narayana, Jing Li, Sabaer Fatehi, John Wieting, Omar Ajmeri, Benigno Uria, Tao Zhu, Yeongil Ko, Laura Knight, Amélie Héliou, Ning Niu, Shane Gu, Chenxi Pang, Dustin Tran, Yeqing Li, Nir Levine, Ariel Stolovich, Norbert Kalb, Rebeca Santamaria-Fernandez, Sonam Goenka, Wenny Yustalim, Robin Strudel, Ali Elqursh, Balaji Lakshminarayanan, Charlie Deck, Shyam Upadhyay, Hyo Lee, Mike Dusenberry, Zonglin Li, Xuezhi Wang, Kyle Levin, Raphael Hoffmann, Dan Holtmann-Rice, Olivier Bachem, Summer Yue, Sho Arora, Eric Malmi, Daniil Mirylenka, Qijun Tan, Christy Koh, Soheil Hassas Yeganeh, Siim Põder, Steven Zheng, Francesco Pongetti, Mukarram Tariq, Yanhua Sun, Lucian Ionita, Mojtaba Seyedhosseini, Pouya Tafti, Ragha Kotikalapudi, Zhiyu Liu, Anmol Gulati, Jasmine Liu, Xinyu Ye, Bart Chrzaszcz, Lily Wang, Nikhil Sethi, Tianrun Li, Ben Brown, Shreya Singh, Wei Fan, Aaron Parisi, Joe Stanton, Chenkai Kuang, Vinod Koverkathu, Christopher A. Choquette-Choo, Yunjie Li, TJ Lu, Abe Ittycheriah, Prakash Shroff, Pei Sun, Mani Varadarajan, Sanaz Bahargam, Rob Willoughby, David Gaddy, Ishita Dasgupta, Guillaume Desjardins, Marco Cornero, Brona Robenek, Bhavishya Mittal, Ben Albrecht, Ashish Shenoy, Fedor Moiseev, Henrik Jacobsson, Alireza Ghaffarkhah, Morgane Rivière, Alanna Walton, Clément Crepy, Alicia Parrish, YuAn Liu, Zongwei Zhou, Clement Farabet, Carey Radebaugh, Praveen Srinivasan, Claudia van der Salm, Andreas Fidjeland, Salvatore Scellato, Eri Latorre-Chimoto, Hanna Klimczak-Plucińska, David Bridson, Dario de Cesare, Tom Hudson, Piermaria Mendolicchio, Lexi Walker, Alex Morris, Ivo Penchev, Matthew Mauger, Alexey Guseynov, Alison Reid, Seth Odoom, Lucia Loher, Victor Cotruta, Madhavi Yenugula, Dominik Grewe, Anastasia Petrushkina, Tom Duerig, Antonio Sanchez, Steve Yadlowsky, Amy Shen, Amir Globerson, Adam Kurzrok, Lynette Webb, Sahil Dua, Dong Li, Preethi Lahoti, Surya Bhupatiraju, Dan Hurt, Haroon Qureshi, Ananth Agarwal, Tomer Shani, Matan Eyal, Anuj Khare, Shreyas Rammohan Belle, Lei Wang, Chetan Tekur, Mihir Sanjay Kale, Jinliang Wei, Ruoxin Sang, Brennan Saeta, Tyler Liechty, Yi Sun, Yao Zhao, Stephan Lee, Pandu Nayak, Doug Fritz, Manish Reddy Vuyyuru, John Aslanides, Nidhi Vyas, Martin Wicke, Xiao Ma, Taylan Bilal, Evgenii Eltyshev, Daniel Balle, Nina Martin, Hardie Cate, James Manyika, Keyvan Amiri, Yelin Kim, Xi Xiong, Kai Kang, Florian Luisier, Nilesh Tripuraneni, David Madras, Mandy Guo, Austin Waters, Oliver Wang, Joshua Ainslie, Jason Baldridge, Han Zhang, Garima Pruthi, Jakob Bauer, Feng Yang, Riham Mansour, Jason Gelman, Yang Xu, George Polovets, Ji Liu, Honglong Cai, Warren Chen, XiangHai Sheng, Emily Xue, Sherjil Ozair, Adams Yu, Christof Angermueller, Xiaowei Li, Weiren Wang, Julia Wiesinger, Emmanouil Koukoumidis, Yuan Tian, Anand Iyer, Madhu Gurumurthy, Mark Goldenson, Parashar Shah, MK Blake, Hongkun Yu, Anthony Urbanowicz, Jennimaria Palomaki, Chrisantha Fernando, Kevin Brooks, Ken Durden, Harsh Mehta, Nikola Momchev, Elahe Rahimtoroghi, Maria Georgaki, Amit Raul, Sebastian Ruder, Morgan Redshaw, Jinhyuk Lee, Komal Jalan, Dinghua Li, Ginger Perng, Blake Hechtman, Parker Schuh, Milad Nasr, Mia Chen, Kieran Milan, Vladimir Mikulik, Trevor Strohman, Juliana Franco, Tim Green, Demis Hassabis, Koray Kavukcuoglu, Jeffrey Dean, Oriol Vinyals

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding.

Arithmetic Reasoning Code Generation +3

(Debiased) Contrastive Learning Loss for Recommendation (Technical Report)

no code implementations13 Dec 2023 Ruoming Jin, Dong Li

In this paper, we perform a systemic examination of the recommendation losses, including listwise (softmax), pairwise(BPR), and pointwise (mean-squared error, MSE, and Cosine Contrastive Loss, CCL) losses through the lens of contrastive learning.

Contrastive Learning

Revisiting Recommendation Loss Functions through Contrastive Learning (Technical Report)

no code implementations13 Dec 2023 Dong Li, Ruoming Jin, Bin Ren

Inspired by the success of contrastive learning, we systematically examine recommendation losses, including listwise (softmax), pairwise (BPR), and pointwise (MSE and CCL) losses.

Contrastive Learning

Semantic-Aware Frame-Event Fusion based Pattern Recognition via Large Vision-Language Models

1 code implementation30 Nov 2023 Dong Li, Jiandong Jin, Yuhao Zhang, Yanlin Zhong, Yaoyang Wu, Lan Chen, Xiao Wang, Bin Luo

Current methods typically employ backbone networks to individually extract the features of RGB frames and event streams, and subsequently fuse these features for pattern recognition.

Language Modelling Prompt Engineering

Optimizing Logical Execution Time Model for Both Determinism and Low Latency

no code implementations30 Oct 2023 Sen Wang, Dong Li, Ashrarul H. Sifat, Shao-Yu Huang, Xuanliang Deng, Changhee Jung, Ryan Williams, Haibo Zeng

Therefore, fLET has the potential to significantly improve the end-to-end timing performance while keeping the benefits of deterministic behavior on timing and dataflow.

HarmonyDream: Task Harmonization Inside World Models

no code implementations30 Sep 2023 Haoyu Ma, Jialong Wu, Ningya Feng, Chenjun Xiao, Dong Li, Jianye Hao, Jianmin Wang, Mingsheng Long

Model-based reinforcement learning (MBRL) holds the promise of sample-efficient learning by utilizing a world model, which models how the environment works and typically encompasses components for two tasks: observation modeling and reward modeling.

Atari Games 100k Model-based Reinforcement Learning +1

Impression-Informed Multi-Behavior Recommender System: A Hierarchical Graph Attention Approach

no code implementations6 Sep 2023 Dong Li, Divya Bhargavi, Vidya Sagar Ravipati

While recommender systems have significantly benefited from implicit feedback, they have often missed the nuances of multi-behavior interactions between users and items.

Graph Attention Graph Sampling +2

Contrastive Representation Learning Based on Multiple Node-centered Subgraphs

no code implementations31 Aug 2023 Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao

As the basic element of graph-structured data, node has been recognized as the main object of study in graph representation learning.

Contrastive Learning Graph Representation Learning

Performance Analysis for Resource Constrained Decentralized Federated Learning Over Wireless Networks

no code implementations12 Aug 2023 Zhigang Yan, Dong Li

Specifically, we provide convergence bounds for both digital and analog transmission approaches, enabling analysis of the model performance trained on DFL.

Federated Learning

Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation

no code implementations7 Aug 2023 Taichi Liu, Chen Gao, Zhenyu Wang, Dong Li, Jianye Hao, Depeng Jin, Yong Li

Graph Neural Network (GNN)-based models have become the mainstream approach for recommender systems.

Recommendation Systems

TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer

2 code implementations27 Jul 2023 Zhen Qin, Dong Li, Weigao Sun, Weixuan Sun, Xuyang Shen, Xiaodong Han, Yunshen Wei, Baohong Lv, Xiao Luo, Yu Qiao, Yiran Zhong

TransNormerLLM evolves from the previous linear attention architecture TransNormer by making advanced modifications that include positional embedding, linear attention acceleration, gating mechanisms, tensor normalization, and inference acceleration and stabilization.

Language Modelling Large Language Model

Event Detection from Social Media Stream: Methods, Datasets and Opportunities

no code implementations28 Jun 2023 Quanzhi Li, Yang Chao, Dong Li, Yao Lu, Chi Zhang

Social media streams contain large and diverse amount of information, ranging from daily-life stories to the latest global and local events and news.

Event Detection

Steganographic Capacity of Deep Learning Models

no code implementations25 Jun 2023 Lei Zhang, Dong Li, Olha Jurečková, Mark Stamp

We find that the steganographic capacity of the learning models tested is surprisingly high, and that in each case, there is a clear threshold after which model performance rapidly degrades.

Malware Classification

Toeplitz Neural Network for Sequence Modeling

2 code implementations8 May 2023 Zhen Qin, Xiaodong Han, Weixuan Sun, Bowen He, Dong Li, Dongxu Li, Yuchao Dai, Lingpeng Kong, Yiran Zhong

Sequence modeling has important applications in natural language processing and computer vision.

Language Modelling Position

Accelerated Fuzzy C-Means Clustering Based on New Affinity Filtering and Membership Scaling

no code implementations14 Feb 2023 Dong Li, Shuisheng Zhou, Witold Pedrycz

However, FCM and its many accelerated variants have low efficiency in the mid-to-late stage of the clustering process.

Clustering

Multi-Prototypes Convex Merging Based K-Means Clustering Algorithm

no code implementations14 Feb 2023 Dong Li, Shuisheng Zhou, Tieyong Zeng, Raymond H. Chan

Specifically, CM can obtain the optimal merging and estimate the correct k. By integrating these two techniques with K-Means algorithm, the proposed MCKM is an efficient and explainable clustering algorithm for escaping the undesirable local minima of K-Means problem without given k first.

Clustering

AttMEMO : Accelerating Transformers with Memoization on Big Memory Systems

no code implementations23 Jan 2023 Yuan Feng, Hyeran Jeon, Filip Blagojevic, Cyril Guyot, Qing Li, Dong Li

Transformer models gain popularity because of their superior inference accuracy and inference throughput.

FDViT: Improve the Hierarchical Architecture of Vision Transformer

no code implementations ICCV 2023 Yixing Xu, Chao Li, Dong Li, Xiao Sheng, Fan Jiang, Lu Tian, Ashish Sirasao

In this paper, we propose FDViT to improve the hierarchical architecture of the vision transformer by using a flexible downsampling layer that is not limited to integer stride to smoothly reduce the sizes of the middle feature maps.

Edge-Aware Regional Message Passing Controller for Image Forgery Localization

no code implementations CVPR 2023 Dong Li, Jiaying Zhu, Menglu Wang, Jiawei Liu, Xueyang Fu, Zheng-Jun Zha

In the second step, guided by the learnable edges, a region message passing controller is devised to weaken the message passing between the forged and authentic regions.

Binarization graph construction

Generation-Augmented Query Expansion For Code Retrieval

no code implementations20 Dec 2022 Dong Li, Yelong Shen, Ruoming Jin, Yi Mao, Kuan Wang, Weizhu Chen

Pre-trained language models have achieved promising success in code retrieval tasks, where a natural language documentation query is given to find the most relevant existing code snippet.

Code Generation Retrieval

State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning

no code implementations28 Nov 2022 Chen Chen, Hongyao Tang, Yi Ma, Chao Wang, Qianli Shen, Dong Li, Jianye Hao

The key idea of SA-PP is leveraging discounted stationary state distribution ratios between the learning policy and the offline dataset to modulate the degree of behavior regularization in a state-wise manner, so that pessimism can be implemented in a more appropriate way.

Offline RL Q-Learning +2

Towards Reliable Item Sampling for Recommendation Evaluation

no code implementations28 Nov 2022 Dong Li, Ruoming Jin, Zhenming Liu, Bin Ren, Jing Gao, Zhi Liu

Since Rendle and Krichene argued that commonly used sampling-based evaluation metrics are "inconsistent" with respect to the global metrics (even in expectation), there have been a few studies on the sampling-based recommender system evaluation.

Recommendation Systems

Prototypical context-aware dynamics generalization for high-dimensional model-based reinforcement learning

no code implementations23 Nov 2022 Junjie Wang, Yao Mu, Dong Li, Qichao Zhang, Dongbin Zhao, Yuzheng Zhuang, Ping Luo, Bin Wang, Jianye Hao

The latent world model provides a promising way to learn policies in a compact latent space for tasks with high-dimensional observations, however, its generalization across diverse environments with unseen dynamics remains challenging.

Model-based Reinforcement Learning reinforcement-learning +1

Linear Video Transformer with Feature Fixation

no code implementations15 Oct 2022 Kaiyue Lu, Zexiang Liu, Jianyuan Wang, Weixuan Sun, Zhen Qin, Dong Li, Xuyang Shen, Hui Deng, Xiaodong Han, Yuchao Dai, Yiran Zhong

Therefore, we propose a feature fixation module to reweight the feature importance of the query and key before computing linear attention.

Feature Importance Video Classification

On the Convergence Theory of Meta Reinforcement Learning with Personalized Policies

no code implementations21 Sep 2022 Haozhi Wang, Qing Wang, Yunfeng Shao, Dong Li, Jianye Hao, Yinchuan Li

Modern meta-reinforcement learning (Meta-RL) methods are mainly developed based on model-agnostic meta-learning, which performs policy gradient steps across tasks to maximize policy performance.

Continuous Control Meta-Learning +3

Mutual Harmony: Sequential Recommendation with Dual Contrastive Network

1 code implementation18 Sep 2022 GuanYu Lin, Chen Gao, Yinfeng Li, Yu Zheng, Zhiheng Li, Depeng Jin, Dong Li, Jianye Hao, Yong Li

Such user-centric recommendation will make it impossible for the provider to expose their new items, failing to consider the accordant interactions between user and item dimensions.

Contrastive Learning Representation Learning +1

Multi-Document Scientific Summarization from a Knowledge Graph-Centric View

1 code implementation COLING 2022 Pancheng Wang, Shasha Li, Kunyuan Pang, Liangliang He, Dong Li, Jintao Tang, Ting Wang

Multi-Document Scientific Summarization (MDSS) aims to produce coherent and concise summaries for clusters of topic-relevant scientific papers.

Descriptive Knowledge Graphs

Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation

no code implementations3 Aug 2022 Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang

More specifically, we propose a novel Coarse-to-fine Knowledge-enhanced Multi-interest Learning (CKML) framework to learn shared and behavior-specific interests for different behaviors.

Neural Architecture Search on Efficient Transformers and Beyond

no code implementations28 Jul 2022 Zexiang Liu, Dong Li, Kaiyue Lu, Zhen Qin, Weixuan Sun, Jiacheng Xu, Yiran Zhong

To address this issue, we propose a new framework to find optimal architectures for efficient Transformers with the neural architecture search (NAS) technique.

Computational Efficiency Image Classification +2

Auto Machine Learning for Medical Image Analysis by Unifying the Search on Data Augmentation and Neural Architecture

no code implementations21 Jul 2022 Jianwei Zhang, Dong Li, Lituan Wang, Lei Zhang

To address the problem, an improved augmentation search strategy, named Augmented Density Matching, was proposed by randomly sampling policies from a prior distribution for training.

AutoML Data Augmentation

Phase Shift Compression for Control Signaling Reduction in IRS-Aided Wireless Systems: Global Attention and Lightweight Design

no code implementations5 Jul 2022 Xianhua Yu, Dong Li

A potential 6G technology known as intelligent reflecting surface (IRS) has recently gained much attention from academia and industry.

SEREN: Knowing When to Explore and When to Exploit

no code implementations30 May 2022 Changmin Yu, David Mguni, Dong Li, Aivar Sootla, Jun Wang, Neil Burgess

Efficient reinforcement learning (RL) involves a trade-off between "exploitative" actions that maximise expected reward and "explorative'" ones that sample unvisited states.

Reinforcement Learning (RL)

Rethinking Reinforcement Learning based Logic Synthesis

no code implementations16 May 2022 Chao Wang, Chen Chen, Dong Li, Bin Wang

Recently, reinforcement learning has been used to address logic synthesis by formulating the operator sequence optimization problem as a Markov decision process.

reinforcement-learning Reinforcement Learning (RL)

Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification

no code implementations CVPR 2022 Haowei Zhu, Wenjing Ke, Dong Li, Ji Liu, Lu Tian, Yi Shan

First, we propose global-local cross-attention (GLCA) to enhance the interactions between global images and local high-response regions, which can help reinforce the spatial-wise discriminative clues for recognition.

Ranked #5 on Fine-Grained Image Classification on CUB-200-2011 (using extra training data)

Fine-Grained Image Classification Fine-Grained Visual Categorization

Dynamic Sparse R-CNN

no code implementations CVPR 2022 Qinghang Hong, Fengming Liu, Dong Li, Ji Liu, Lu Tian, Yi Shan

Sparse R-CNN is a recent strong object detection baseline by set prediction on sparse, learnable proposal boxes and proposal features.

object-detection Object Detection

Compare learning: bi-attention network for few-shot learning

no code implementations25 Mar 2022 Li Ke, Meng Pan, Weigao Wen, Dong Li

Learning with few labeled data is a key challenge for visual recognition, as deep neural networks tend to overfit using a few samples only.

Few-Shot Learning Metric Learning

Breaking the Curse of Dimensionality in Multiagent State Space: A Unified Agent Permutation Framework

no code implementations10 Mar 2022 Xiaotian Hao, Hangyu Mao, Weixun Wang, Yaodong Yang, Dong Li, Yan Zheng, Zhen Wang, Jianye Hao

To break this curse, we propose a unified agent permutation framework that exploits the permutation invariance (PI) and permutation equivariance (PE) inductive biases to reduce the multiagent state space.

Data Augmentation Reinforcement Learning (RL) +1

Who Should Review Your Proposal? Interdisciplinary Topic Path Detection for Research Proposals

no code implementations7 Mar 2022 Meng Xiao, Ziyue Qiao, Yanjie Fu, Hao Dong, Yi Du, Pengyang Wang, Dong Li, Yuanchun Zhou

After extracting the semantic and interdisciplinary knowledge, we design a level-wise prediction component to fuse the two types of knowledge representations and detect interdisciplinary topic paths for each proposal.

Representing Videos as Discriminative Sub-graphs for Action Recognition

no code implementations CVPR 2021 Dong Li, Zhaofan Qiu, Yingwei Pan, Ting Yao, Houqiang Li, Tao Mei

For each action category, we execute online clustering to decompose the graph into sub-graphs on each scale through learning Gaussian Mixture Layer and select the discriminative sub-graphs as action prototypes for recognition.

Action Recognition Graph Learning +1

Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning

no code implementations31 Dec 2021 Xiang Li, Dong Li, Ruoming Jin, Gagan Agrawal, Rajiv Ramnath

Though other methods (particularly those based on Laplacian Smoothing) have reported better accuracy, a fundamental limitation of all the work is a lack of scalability.

Clustering Deep Clustering +3

A Survey on Interpretable Reinforcement Learning

no code implementations24 Dec 2021 Claire Glanois, Paul Weng, Matthieu Zimmer, Dong Li, Tianpei Yang, Jianye Hao, Wulong Liu

To that aim, we distinguish interpretability (as a property of a model) and explainability (as a post-hoc operation, with the intervention of a proxy) and discuss them in the context of RL with an emphasis on the former notion.

Autonomous Driving Decision Making +2

Learning State Representations via Retracing in Reinforcement Learning

1 code implementation ICLR 2022 Changmin Yu, Dong Li, Jianye Hao, Jun Wang, Neil Burgess

We propose learning via retracing, a novel self-supervised approach for learning the state representation (and the associated dynamics model) for reinforcement learning tasks.

Continuous Control Model-based Reinforcement Learning +3

SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition

no code implementations17 Nov 2021 Hangyu Mao, Chao Wang, Xiaotian Hao, Yihuan Mao, Yiming Lu, Chengjie WU, Jianye Hao, Dong Li, Pingzhong Tang

The MineRL competition is designed for the development of reinforcement learning and imitation learning algorithms that can efficiently leverage human demonstrations to drastically reduce the number of environment interactions needed to solve the complex \emph{ObtainDiamond} task with sparse rewards.

Imitation Learning reinforcement-learning +1

Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction

no code implementations10 Nov 2021 Amur Ghose, Vincent Zhang, Yingxue Zhang, Dong Li, Wulong Liu, Mark Coates

To address this limitation, we propose a framework that can directly learn embeddings for the given netlist to enhance the quality of our node features.

Graph Embedding

Convolutional Autoencoder-Based Phase Shift Feedback Compression for Intelligent Reflecting Surface-Assisted Wireless Systems

1 code implementation24 Oct 2021 Xianhua Yu, Dong Li, Yongjun Xu, Ying-Chang Liang

To this end, it is crucial to adjust the phases of reflecting elements of the IRS, and most of the research works focus on how to optimize/quantize the phase for different optimization objectives.

Quantization

Ranking Cost: Building An Efficient and Scalable Circuit Routing Planner with Evolution-Based Optimization

1 code implementation8 Oct 2021 Shiyu Huang, Bin Wang, Dong Li, Jianye Hao, Ting Chen, Jun Zhu

In this work, we propose a new algorithm for circuit routing, named Ranking Cost, which innovatively combines search-based methods (i. e., A* algorithm) and learning-based methods (i. e., Evolution Strategies) to form an efficient and trainable router.

Learning Pseudometric-based Action Representations for Offline Reinforcement Learning

no code implementations29 Sep 2021 Pengjie Gu, Mengchen Zhao, Chen Chen, Dong Li, Jianye Hao, Bo An

Offline reinforcement learning is a promising approach for practical applications since it does not require interactions with real-world environments.

Offline RL Recommendation Systems +4

Learning Explicit Credit Assignment for Multi-agent Joint Q-learning

no code implementations29 Sep 2021 Hangyu Mao, Jianye Hao, Dong Li, Jun Wang, Weixun Wang, Xiaotian Hao, Bin Wang, Kun Shao, Zhen Xiao, Wulong Liu

In contrast, we formulate an \emph{explicit} credit assignment problem where each agent gives its suggestion about how to weight individual Q-values to explicitly maximize the joint Q-value, besides guaranteeing the Bellman optimality of the joint Q-value.

Q-Learning

On the regularization landscape for the linear recommendation models

no code implementations29 Sep 2021 Dong Li, Zhenming Liu, Ruoming Jin, Zhi Liu, Jing Gao, Bin Ren

Recently, a wide range of recommendation algorithms inspired by deep learning techniques have emerged as the performance leaders several standard recommendation benchmarks.

CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation

no code implementations24 Aug 2021 Xidong Feng, Chen Chen, Dong Li, Mengchen Zhao, Jianye Hao, Jun Wang

Meta learning, especially gradient based one, can be adopted to tackle this problem by learning initial parameters of the model and thus allowing fast adaptation to a specific task from limited data examples.

Computational Efficiency Meta-Learning +1

On Sampling Top-K Recommendation Evaluation

no code implementations20 Jun 2021 Dong Li, Ruoming Jin, Jing Gao, Zhi Liu

Recently, Rendle has warned that the use of sampling-based top-$k$ metrics might not suffice.

RankDetNet: Delving Into Ranking Constraints for Object Detection

no code implementations CVPR 2021 Ji Liu, Dong Li, Rongzhang Zheng, Lu Tian, Yi Shan

To this end, we comprehensively investigate three types of ranking constraints, i. e., global ranking, class-specific ranking and IoU-guided ranking losses.

3D Object Detection Classification +3

Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment

no code implementations1 Jun 2021 Tianze Zhou, Fubiao Zhang, Kun Shao, Kai Li, Wenhan Huang, Jun Luo, Weixun Wang, Yaodong Yang, Hangyu Mao, Bin Wang, Dong Li, Wulong Liu, Jianye Hao

In addition, we use a novel agent network named Population Invariant agent with Transformer (PIT) to realize the coordination transfer in more varieties of scenarios.

Management Multi-agent Reinforcement Learning +3

Towards a Better Understanding of Linear Models for Recommendation

no code implementations27 May 2021 Ruoming Jin, Dong Li, Jing Gao, Zhi Liu, Li Chen, Yang Zhou

Through the derivation and analysis of the closed-form solutions for two basic regression and matrix factorization approaches, we found these two approaches are indeed inherently related but also diverge in how they "scale-down" the singular values of the original user-item interaction matrix.

regression

Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving

no code implementations21 Mar 2021 Li Wang, Dong Li, Han Liu, Jinzhang Peng, Lu Tian, Yi Shan

Our goal is to train a unified model for improving the performance in each dataset by leveraging information from all the datasets.

3D Semantic Segmentation Autonomous Driving +3

Learning Symbolic Rules for Interpretable Deep Reinforcement Learning

no code implementations15 Mar 2021 Zhihao Ma, Yuzheng Zhuang, Paul Weng, Hankz Hankui Zhuo, Dong Li, Wulong Liu, Jianye Hao

To address this challenge and improve the transparency, we propose a Neural Symbolic Reinforcement Learning framework by introducing symbolic logic into DRL.

reinforcement-learning Reinforcement Learning (RL)

On Estimating Recommendation Evaluation Metrics under Sampling

no code implementations2 Mar 2021 Ruoming Jin, Dong Li, Benjamin Mudrak, Jing Gao, Zhi Liu

The proposed approaches either are rather uninformative (linking sampling to metric evaluation) or can only work on simple metrics, such as Recall/Precision (Krichene and Rendle 2020; Li et al. 2020).

Differentiable Logic Machines

no code implementations23 Feb 2021 Matthieu Zimmer, Xuening Feng, Claire Glanois, Zhaohui Jiang, Jianyi Zhang, Paul Weng, Dong Li, Jianye Hao, Wulong Liu

As a step in this direction, we propose a novel neural-logic architecture, called differentiable logic machine (DLM), that can solve both inductive logic programming (ILP) and reinforcement learning (RL) problems, where the solution can be interpreted as a first-order logic program.

Decision Making Inductive logic programming +1

Excess-noise suppression for a squeezed state propagating through random amplifying media via wave-front shaping

no code implementations4 Feb 2021 Dong Li, Song Sun, Yao Yao

After propagating through a random amplifying medium, a squeezed state commonly shows excess noise above the shot-noise level.

Quantum Physics

Diagnosing a Solar Flaring Core with Bidirectional Quasi-Periodic Fast Propagating Magnetoacoustic Waves

no code implementations29 Jan 2021 Yuhu Miao, Dong Li, Ding Yuan, Chaowei Jiang, Abouazza Elmhamdi, Mingyu Zhao, Sergey Anfinogentov

Quasi-periodic fast propagating (QFP) waves are often excited by solar flares, and could be trapped in the coronal structure with low Alfv\'en speed, so they could be used as a diagnosing tool for both the flaring core and magnetic waveguide.

Solar and Stellar Astrophysics

ZeRO-Offload: Democratizing Billion-Scale Model Training

3 code implementations18 Jan 2021 Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, Olatunji Ruwase, Shuangyan Yang, Minjia Zhang, Dong Li, Yuxiong He

By combining compute and memory efficiency with ease-of-use, ZeRO-Offload democratizes large-scale model training making it accessible to even data scientists with access to just a single GPU.

Computational Efficiency

Robust Multi-Agent Reinforcement Learning Driven by Correlated Equilibrium

no code implementations1 Jan 2021 Yizheng Hu, Kun Shao, Dong Li, Jianye Hao, Wulong Liu, Yaodong Yang, Jun Wang, Zhanxing Zhu

Therefore, to achieve robust CMARL, we introduce novel strategies to encourage agents to learn correlated equilibrium while maximally preserving the convenience of the decentralized execution.

Adversarial Robustness reinforcement-learning +2

Improving Low-Precision Network Quantization via Bin Regularization

no code implementations ICCV 2021 Tiantian Han, Dong Li, Ji Liu, Lu Tian, Yi Shan

Such bin regularization (BR) mechanism encourages the weight distribution of each quantization bin to be sharp and approximate to a Dirac delta distribution ideally.

Quantization

Meta-Learning with Implicit Processes

no code implementations1 Jan 2021 Yizhou Chen, Dong Li, Na Li, TONG LIANG, Shizhuo Zhang, Bryan Kian Hsiang Low

This paper presents a novel implicit process-based meta-learning (IPML) algorithm that, in contrast to existing works, explicitly represents each task as a continuous latent vector and models its probabilistic belief within the highly expressive IP framework.

Meta-Learning

Ranking Cost: One-Stage Circuit Routing by Directly Optimizing Global Objective Function

no code implementations1 Jan 2021 Shiyu Huang, Bin Wang, Dong Li, Jianye Hao, Jun Zhu, Ting Chen

In our method, we introduce a new set of variables called cost maps, which can help the A* router to find out proper paths to achieve the global object.

Approximating Pareto Frontier through Bayesian-optimization-directed Robust Multi-objective Reinforcement Learning

no code implementations1 Jan 2021 Xiangkun He, Jianye Hao, Dong Li, Bin Wang, Wulong Liu

Thirdly, the agent’s learning process is regarded as a black-box, and the comprehensive metric we proposed is computed after each episode of training, then a Bayesian optimization (BO) algorithm is adopted to guide the agent to evolve towards improving the quality of the approximated Pareto frontier.

Bayesian Optimization Multi-Objective Reinforcement Learning +1

Strong but Simple Baseline with Dual-Granularity Triplet Loss for Visible-Thermal Person Re-Identification

1 code implementation9 Dec 2020 Haijun Liu, Yanxia Chai, Xiaoheng Tan, Dong Li, Xichuan Zhou

In this letter, we propose a conceptually simple and effective dual-granularity triplet loss for visible-thermal person re-identification (VT-ReID).

Cross-Modal Person Re-Identification

Towards Better Object Detection in Scale Variation with Adaptive Feature Selection

1 code implementation6 Dec 2020 Zehui Gong, Dong Li

It is a common practice to exploit pyramidal feature representation to tackle the problem of scale variation in object instances.

feature selection object-detection +1

HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory

no code implementations NeurIPS 2020 Jie Ren, Minjia Zhang, Dong Li

The emergence of heterogeneous memory (HM) brings a solution to significantly increase memory capacity and break the above tradeoff: Using HM, billions of data points can be placed in the main memory on a single machine without using any data compression.

Data Compression Quantization

What About Inputing Policy in Value Function: Policy Representation and Policy-extended Value Function Approximator

no code implementations NeurIPS 2021 Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Changmin Yu, Hangyu Mao, Wulong Liu, Yaodong Yang, Wenyuan Tao, Li Wang

We study Policy-extended Value Function Approximator (PeVFA) in Reinforcement Learning (RL), which extends conventional value function approximator (VFA) to take as input not only the state (and action) but also an explicit policy representation.

Continuous Control Contrastive Learning +3

Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed

1 code implementation14 Oct 2020 Dong Li, Sitong Chen, Xudong Liu, YunDa Sun, Li Zhang

In this paper, we propose a balanced filter pruning method for both performance and pruning speed.

Adaptive Neural Network-Based Approximation to Accelerate Eulerian Fluid Simulation

no code implementations26 Aug 2020 Wenqian Dong, Jie Liu, Zhen Xie, Dong Li

Evaluating with 20, 480 input problems, we show that Smartfluidnet achieves 1. 46x and 590x speedup comparing with a state-of-the-art neural network model and the original fluid simulation respectively on an NVIDIA Titan X Pascal GPU, while providing better simulation quality than the state-of-the-art model.

Smart-PGSim: Using Neural Network to Accelerate AC-OPF Power Grid Simulation

no code implementations26 Aug 2020 Wenqian Dong, Zhen Xie, Gokcen Kestor, Dong Li

In this paper, we develop a neural network approach to the problem of accelerating the current optimal power flow (AC-OPF) by generating an intelligent initial solution.

Scheduling

Long Short-Term Relation Networks for Video Action Detection

no code implementations31 Mar 2020 Dong Li, Ting Yao, Zhaofan Qiu, Houqiang Li, Tao Mei

It has been well recognized that modeling human-object or object-object relations would be helpful for detection task.

Action Detection Object +2

Feedback Graph Convolutional Network for Skeleton-based Action Recognition

no code implementations17 Mar 2020 Hao Yang, Dan Yan, Li Zhang, Dong Li, YunDa Sun, ShaoDi You, Stephen J. Maybank

It transmits the high-level semantic features to the low-level layers and flows temporal information stage by stage to progressively model global spatial-temporal features for action recognition; (3) The FGCN model provides early predictions.

Action Recognition Skeleton Based Action Recognition

FLAME: A Self-Adaptive Auto-labeling System for Heterogeneous Mobile Processors

no code implementations3 Mar 2020 Jie Liu, Jiawen Liu, Zhen Xie, Dong Li

How to accurately and efficiently label data on a mobile device is critical for the success of training machine learning models on mobile devices.

Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning

no code implementations3 Dec 2019 Hangyu Mao, Wulong Liu, Jianye Hao, Jun Luo, Dong Li, Zhengchao Zhang, Jun Wang, Zhen Xiao

Social psychology and real experiences show that cognitive consistency plays an important role to keep human society in order: if people have a more consistent cognition about their environments, they are more likely to achieve better cooperation.

Multi-agent Reinforcement Learning Q-Learning +2

Spam Review Detection with Graph Convolutional Networks

3 code implementations22 Aug 2019 Ao Li, Zhou Qin, Runshi Liu, Yiqun Yang, Dong Li

Furthermore, we deploy our system to process million-scale data daily at Xianyu.

MVB: A Large-Scale Dataset for Baggage Re-Identification and Merged Siamese Networks

2 code implementations26 Jul 2019 Zhulin Zhang, Dong Li, Jinhua Wu, YunDa Sun, Li Zhang

Second, all baggage images are captured by specially-designed multi-view camera system to handle pose variation and occlusion, in order to obtain the 3D information of baggage surface as complete as possible.

Zero-Shot Video Question Answer

Combining Q&A Pair Quality and Question Relevance Features on Community-based Question Retrieval

no code implementations3 Jul 2019 Dong Li, Lin Li

The Q&A community has become an important way for people to access knowledge and information from the Internet.

Retrieval Translation

Trimmed Action Recognition, Dense-Captioning Events in Videos, and Spatio-temporal Action Localization with Focus on ActivityNet Challenge 2019

no code implementations14 Jun 2019 Zhaofan Qiu, Dong Li, Yehao Li, Qi Cai, Yingwei Pan, Ting Yao

This notebook paper presents an overview and comparative analysis of our systems designed for the following three tasks in ActivityNet Challenge 2019: trimmed action recognition, dense-captioning events in videos, and spatio-temporal action localization.

Action Recognition Dense Captioning +2

Performance Analysis and Characterization of Training Deep Learning Models on Mobile Devices

no code implementations10 Jun 2019 Jie Liu, Jiawen Liu, Wan Du, Dong Li

In this paper, we perform a variety of experiments on a representative mobile device (the NVIDIA TX2) to study the performance of training deep learning models.

Graph Attention Memory for Visual Navigation

no code implementations11 May 2019 Dong Li, Qichao Zhang, Dongbin Zhao, Yuzheng Zhuang, Bin Wang, Wulong Liu, Rasul Tutunov, Jun Wang

To address the long-term memory issue, this paper proposes a graph attention memory (GAM) architecture consisting of memory construction module, graph attention module and control module.

Graph Attention Reinforcement Learning (RL) +1

A Preliminary Study of Neural Network-based Approximation for HPC Applications

1 code implementation18 Dec 2018 Wenqian Dong, Anzheng Guolu, Dong Li

Machine learning, as a tool to learn and model complicated (non)linear relationships between input and output data sets, has shown preliminary success in some HPC problems.

BIG-bench Machine Learning

Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections

1 code implementation22 Nov 2018 Jian-Feng Cai, Dong Li, Jiaze Sun, Ke Wang

The key in our proof is that random projections embed stably the set of sparse vectors or a low-dimensional smooth manifold into a low-dimensional subspace.

Dimensionality Reduction

Reinforcement Learning and Deep Learning based Lateral Control for Autonomous Driving

1 code implementation30 Oct 2018 Dong Li, Dongbin Zhao, Qichao Zhang, Yaran Chen

The control module which is based on reinforcement learning then makes a control decision based on these features.

Autonomous Driving Model Predictive Control +3

Runtime Concurrency Control and Operation Scheduling for High Performance Neural Network Training

no code implementations21 Oct 2018 Jiawen Liu, Dong Li, Gokcen Kestor, Jeffrey Vetter

These frameworks employ a dataflow model where the NN training is modeled as a directed graph composed of a set of nodes.

BIG-bench Machine Learning Scheduling

Recurrent Tubelet Proposal and Recognition Networks for Action Detection

no code implementations ECCV 2018 Dong Li, Zhaofan Qiu, Qi Dai, Ting Yao, Tao Mei

The RTP initializes action proposals of the start frame through a Region Proposal Network and then estimates the movements of proposals in next frame in a recurrent manner.

Action Detection Region Proposal

Baidu Apollo EM Motion Planner

1 code implementation20 Jul 2018 Haoyang Fan, Fan Zhu, Changchun Liu, Liangliang Zhang, Li Zhuang, Dong Li, Weicheng Zhu, Jiangtao Hu, Hongye Li, Qi Kong

In this manuscript, we introduce a real-time motion planning system based on the Baidu Apollo (open source) autonomous driving platform.

Autonomous Driving Motion Planning

Progressive Representation Adaptation for Weakly Supervised Object Localization

1 code implementation12 Oct 2017 Dong Li, Jia-Bin Huang, Ya-Li Li, Shengjin Wang, Ming-Hsuan Yang

In classification adaptation, we transfer a pre-trained network to a multi-label classification task for recognizing the presence of a certain object in an image.

Classification General Classification +4

Joint Maximum Purity Forest with Application to Image Super-Resolution

1 code implementation30 Aug 2017 Hailiang Li, Kin-Man Lam, Dong Li

In the JMPF scheme, the original feature space is transformed into a compactly pre-clustered feature space, via a trained rotation matrix.

Clustering General Classification +3

Learning Structured Semantic Embeddings for Visual Recognition

no code implementations5 Jun 2017 Dong Li, Hsin-Ying Lee, Jia-Bin Huang, Shengjin Wang, Ming-Hsuan Yang

First, we exploit the discriminative constraints to capture the intra- and inter-class relationships of image embeddings.

General Classification Multi-Label Classification +2

Weakly Supervised Object Localization With Progressive Domain Adaptation

no code implementations CVPR 2016 Dong Li, Jia-Bin Huang, Ya-Li Li, Shengjin Wang, Ming-Hsuan Yang

In this paper, we address this problem by progressive domain adaptation with two main steps: classification adaptation and detection adaptation.

Classification Domain Adaptation +5

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