Search Results for author: Tao Li

Found 124 papers, 42 papers with code

Convergence Conditions of Online Regularized Statistical Learning in Reproducing Kernel Hilbert Space With Non-Stationary Data

no code implementations4 Apr 2024 Xiwei Zhang, Tao Li

Furthermore, if the data streams also satisfy the RKHS persistence of excitation condition, i. e. there exists a fixed length of time period, such that each eigenvalue of the conditional expectation of the operators induced by the input data accumulated over every time period has a uniformly positive lower bound with respect to time, then the output of the algorithm is consistent with the unknown function in mean square.

Minimize Quantization Output Error with Bias Compensation

1 code implementation2 Apr 2024 Cheng Gong, Haoshuai Zheng, Mengting Hu, Zheng Lin, Deng-Ping Fan, Yuzhi Zhang, Tao Li

Quantization is a promising method that reduces memory usage and computational intensity of Deep Neural Networks (DNNs), but it often leads to significant output error that hinder model deployment.


Revisiting Random Weight Perturbation for Efficiently Improving Generalization

1 code implementation30 Mar 2024 Tao Li, Qinghua Tao, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Mingzhen He, Xiaolin Huang

Improving the generalization ability of modern deep neural networks (DNNs) is a fundamental challenge in machine learning.

Friendly Sharpness-Aware Minimization

1 code implementation19 Mar 2024 Tao Li, Pan Zhou, Zhengbao He, Xinwen Cheng, Xiaolin Huang

By decomposing the adversarial perturbation in SAM into full gradient and stochastic gradient noise components, we discover that relying solely on the full gradient component degrades generalization while excluding it leads to improved performance.

Symbiotic Game and Foundation Models for Cyber Deception Operations in Strategic Cyber Warfare

no code implementations14 Mar 2024 Tao Li, Quanyan Zhu

This chapter concludes with a discussion of the challenges associated with FMs and their application in the domain of cybersecurity.

Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games

no code implementations29 Feb 2024 Tao Li, Kim Hammar, Rolf Stadler, Quanyan Zhu

To address these limitations, we propose conjectural online learning (\textsc{col}), an online method for generic \textsc{aisg}s. \textsc{col} uses a forecaster-actor-critic (\textsc{fac}) architecture where subjective forecasts are used to conjecture the opponents' strategies within a lookahead horizon, and Bayesian learning is used to calibrate the conjectures.

Decision Making

Automated Security Response through Online Learning with Adaptive Conjectures

no code implementations19 Feb 2024 Kim Hammar, Tao Li, Rolf Stadler, Quanyan Zhu

We study automated security response for an IT infrastructure and formulate the interaction between an attacker and a defender as a partially observed, non-stationary game.

MM-TTS: Multi-modal Prompt based Style Transfer for Expressive Text-to-Speech Synthesis

no code implementations17 Dec 2023 Wenhao Guan, Yishuang Li, Tao Li, Hukai Huang, Feng Wang, Jiayan Lin, Lingyan Huang, Lin Li, Qingyang Hong

The challenges of modeling such a multi-modal style controllable TTS mainly lie in two aspects:1)aligning the multi-modal information into a unified style space to enable the input of arbitrary modality as the style prompt in a single system, and 2)efficiently transferring the unified style representation into the given text content, thereby empowering the ability to generate prompt style-related voice.

Speech Synthesis Style Transfer +1

Towards Inductive Robustness: Distilling and Fostering Wave-induced Resonance in Transductive GCNs Against Graph Adversarial Attacks

no code implementations14 Dec 2023 Ao Liu, Wenshan Li, Tao Li, Beibei Li, Hanyuan Huang, Pan Zhou

We then prove that merely three MP iterations within GCNs can induce signal resonance between nodes and edges, manifesting as a coupling between nodes and their distillable surrounding local subgraph.

Generalizable Sleep Staging via Multi-Level Domain Alignment

1 code implementation13 Dec 2023 Jiquan Wang, Sha Zhao, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan

In this paper, we introduce domain generalization into automatic sleep staging and propose the task of generalizable sleep staging which aims to improve the model generalization ability to unseen datasets.

Domain Generalization Sleep Staging

Online Continual Learning via Logit Adjusted Softmax

1 code implementation11 Nov 2023 Zhehao Huang, Tao Li, Chenhe Yuan, Yingwen Wu, Xiaolin Huang

Online continual learning is a challenging problem where models must learn from a non-stationary data stream while avoiding catastrophic forgetting.

Continual Learning

Towards Generalized Multi-stage Clustering: Multi-view Self-distillation

no code implementations29 Oct 2023 Jiatai Wang, Zhiwei Xu, Xin Wang, Tao Li

MVC aims at exploring common semantics and pseudo-labels from multiple views and clustering in a self-supervised manner.

Clustering Contrastive Learning +1

Lifting the Veil: Unlocking the Power of Depth in Q-learning

no code implementations27 Oct 2023 Shao-Bo Lin, Tao Li, Shaojie Tang, Yao Wang, Ding-Xuan Zhou

In this paper, we make fundamental contributions to the field of reinforcement learning by answering to the following three questions: Why does deep Q-learning perform so well?

Learning Theory Management +2

Low-Dimensional Gradient Helps Out-of-Distribution Detection

no code implementations26 Oct 2023 Yingwen Wu, Tao Li, Xinwen Cheng, Jie Yang, Xiaolin Huang

To bridge this gap, in this paper, we conduct a comprehensive investigation into leveraging the entirety of gradient information for OOD detection.

Dimensionality Reduction Out-of-Distribution Detection

Bayesian Domain Invariant Learning via Posterior Generalization of Parameter Distributions

no code implementations25 Oct 2023 Shiyu Shen, Bin Pan, Tianyang Shi, Tao Li, Zhenwei Shi

We first propose a theorem to show that the invariant posterior of parameters can be implicitly inferred by aggregating posteriors on different training domains.

Domain Generalization Variational Inference

Be Bayesian by Attachments to Catch More Uncertainty

no code implementations19 Oct 2023 Shiyu Shen, Bin Pan, Tianyang Shi, Tao Li, Zhenwei Shi

Bayesian Neural Networks (BNNs) have become one of the promising approaches for uncertainty estimation due to the solid theorical foundations.

A Zero-Shot Language Agent for Computer Control with Structured Reflection

no code implementations12 Oct 2023 Tao Li, Gang Li, Zhiwei Deng, Bryan Wang, Yang Li

To perform a task, recent works often require a model to learn from trace examples of the task via either supervised learning or few/many-shot prompting.


Automatic Macro Mining from Interaction Traces at Scale

no code implementations10 Oct 2023 Forrest Huang, Gang Li, Tao Li, Yang Li

Macros are building block tasks of our everyday smartphone activity (e. g., "login", or "booking a flight").

Self-Confirming Transformer for Locally Consistent Online Adaptation in Multi-Agent Reinforcement Learning

no code implementations6 Oct 2023 Tao Li, Juan Guevara, Xinghong Xie, Quanyan Zhu

In the multi-agent RL (MARL) setting, this distribution shift may arise from the nonstationary opponents (exogenous agents beyond control) in the online testing who display distinct behaviors from those recorded in the offline dataset.

Multi-agent Reinforcement Learning Offline RL +1

Investigating Shift Equivalence of Convolutional Neural Networks in Industrial Defect Segmentation

1 code implementation29 Sep 2023 Zhen Qu, Xian Tao, Fei Shen, Zhengtao Zhang, Tao Li

In industrial defect segmentation tasks, while pixel accuracy and Intersection over Union (IoU) are commonly employed metrics to assess segmentation performance, the output consistency (also referred to equivalence) of the model is often overlooked.

Data Augmentation Segmentation

MSM-VC: High-fidelity Source Style Transfer for Non-Parallel Voice Conversion by Multi-scale Style Modeling

no code implementations3 Sep 2023 Zhichao Wang, Xinsheng Wang, Qicong Xie, Tao Li, Lei Xie, Qiao Tian, Yuping Wang

In addition to conveying the linguistic content from source speech to converted speech, maintaining the speaking style of source speech also plays an important role in the voice conversion (VC) task, which is essential in many scenarios with highly expressive source speech, such as dubbing and data augmentation.

Data Augmentation Disentanglement +3

Spiking-Diffusion: Vector Quantized Discrete Diffusion Model with Spiking Neural Networks

1 code implementation20 Aug 2023 Mingxuan Liu, Jie Gan, Rui Wen, Tao Li, Yongli Chen, Hong Chen

To fill the gap, we propose a Spiking-Diffusion model, which is based on the vector quantized discrete diffusion model.

Image Generation

METTS: Multilingual Emotional Text-to-Speech by Cross-speaker and Cross-lingual Emotion Transfer

no code implementations29 Jul 2023 Xinfa Zhu, Yi Lei, Tao Li, Yongmao Zhang, Hongbin Zhou, Heng Lu, Lei Xie

However, such data-efficient approaches have ignored synthesizing emotional aspects of speech due to the challenges of cross-speaker cross-lingual emotion transfer - the heavy entanglement of speaker timbre, emotion, and language factors in the speech signal will make a system produce cross-lingual synthetic speech with an undesired foreign accent and weak emotion expressiveness.

Disentanglement Quantization +1

DVPT: Dynamic Visual Prompt Tuning of Large Pre-trained Models for Medical Image Analysis

no code implementations19 Jul 2023 Along He, Kai Wang, Zhihong Wang, Tao Li, Huazhu Fu

Firstly, the frozen features are transformed by an lightweight bottleneck layer to learn the domain-specific distribution of downstream medical tasks, and then a few learnable visual prompts are used as dynamic queries and then conduct cross-attention with the transformed features, attempting to acquire sample-specific knowledge that are suitable for each sample.

Visual Prompt Tuning

A First Order Meta Stackelberg Method for Robust Federated Learning

no code implementations23 Jun 2023 Yunian Pan, Tao Li, Henger Li, Tianyi Xu, Zizhan Zheng, Quanyan Zhu

Previous research has shown that federated learning (FL) systems are exposed to an array of security risks.

Federated Learning Meta-Learning +1

Zero-Shot Wireless Indoor Navigation through Physics-Informed Reinforcement Learning

1 code implementation11 Jun 2023 Mingsheng Yin, Tao Li, Haozhe Lei, Yaqi Hu, Sundeep Rangan, Quanyan Zhu

To equip the navigation agent with sample-efficient learning and {zero-shot} generalization, this work proposes a novel physics-informed RL (PIRL) where a distance-to-target-based cost (standard in e2e) is augmented with physics-informed reward shaping.

Navigate reinforcement-learning +3

Importance Sparsification for Sinkhorn Algorithm

1 code implementation11 Jun 2023 Mengyu Li, Jun Yu, Tao Li, Cheng Meng

Sinkhorn algorithm has been used pervasively to approximate the solution to optimal transport (OT) and unbalanced optimal transport (UOT) problems.

Learning Semantic Role Labeling from Compatible Label Sequences

1 code implementation24 May 2023 Tao Li, Ghazaleh Kazeminejad, Susan W. Brown, Martha Palmer, Vivek Srikumar

In this paper, we eliminate such issue with a framework that jointly models VerbNet and PropBank labels as one sequence.

Domain Generalization Semantic Role Labeling

Accurate ignition detection of solid fuel particles using machine learning

no code implementations20 Apr 2023 Tao Li, Zhangke Liang, Andreas Dreizler, Benjamin Böhm

In the present work, accurate determination of single-particle ignition is focused on using high-speed optical diagnostics combined with machine learning approaches.

AutoQNN: An End-to-End Framework for Automatically Quantizing Neural Networks

no code implementations7 Apr 2023 Cheng Gong, Ye Lu, Surong Dai, Deng Qian, Chenkun Du, Tao Li

QSS introduces five quantizing schemes and defines three new schemes as a candidate set for scheme search, and then uses the differentiable neural architecture search (DNAS) algorithm to seek the layer- or model-desired scheme from the set.

Neural Architecture Search Quantization

Is Stochastic Mirror Descent Vulnerable to Adversarial Delay Attacks? A Traffic Assignment Resilience Study

no code implementations3 Apr 2023 Yunian Pan, Tao Li, Quanyan Zhu

\textit{Intelligent Navigation Systems} (INS) are exposed to an increasing number of informational attack vectors, which often intercept through the communication channels between the INS and the transportation network during the data collecting process.

Random Inverse Problems Over Graphs: Decentralized Online Learning

no code implementations20 Mar 2023 Tao Li, Xiwei Zhang

Moreover, we propose a decentralized online learning algorithm in RKHS based on non-stationary and non-independent online data streams, and prove that the algorithm is mean square and almost surely strongly consistent if the operators induced by the random input data satisfy the infinite-dimensional spatio-temporal persistence of excitation condition.

Scenario-Agnostic Zero-Trust Defense with Explainable Threshold Policy: A Meta-Learning Approach

no code implementations6 Mar 2023 Yunfei Ge, Tao Li, Quanyan Zhu

The increasing connectivity and intricate remote access environment have made traditional perimeter-based network defense vulnerable.

Decision Making Meta-Learning

Investigating Catastrophic Overfitting in Fast Adversarial Training: A Self-fitting Perspective

no code implementations23 Feb 2023 Zhengbao He, Tao Li, Sizhe Chen, Xiaolin Huang

Based on self-fitting, we provide new insights into the existing methods to mitigate CO and extend CO to multi-step adversarial training.


Commitment with Signaling under Double-sided Information Asymmetry

no code implementations22 Dec 2022 Tao Li, Quanyan Zhu

This work considers a double-sided information asymmetry in a Bayesian Stackelberg game, where the leader's realized action, sampled from the mixed strategy commitment, is hidden from the follower.

An Extensible Plug-and-Play Method for Multi-Aspect Controllable Text Generation

1 code implementation19 Dec 2022 Xuancheng Huang, Zijun Liu, Peng Li, Tao Li, Maosong Sun, Yang Liu

Recently, multi-aspect controllable text generation that controls the generated text in multiple aspects (e. g., sentiment, topic, and keywords) has attracted increasing attention.

Machine Translation Text Generation +1

Efficient Generalization Improvement Guided by Random Weight Perturbation

1 code implementation21 Nov 2022 Tao Li, Weihao Yan, Zehao Lei, Yingwen Wu, Kun Fang, Ming Yang, Xiaolin Huang

To fully uncover the great potential of deep neural networks (DNNs), various learning algorithms have been developed to improve the model's generalization ability.

On Multi-head Ensemble of Smoothed Classifiers for Certified Robustness

1 code implementation20 Nov 2022 Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Xiaolin Huang, Jie Yang

Randomized Smoothing (RS) is a promising technique for certified robustness, and recently in RS the ensemble of multiple deep neural networks (DNNs) has shown state-of-the-art performances.

Multi-Speaker Expressive Speech Synthesis via Multiple Factors Decoupling

no code implementations19 Nov 2022 Xinfa Zhu, Yi Lei, Kun Song, Yongmao Zhang, Tao Li, Lei Xie

This paper aims to synthesize the target speaker's speech with desired speaking style and emotion by transferring the style and emotion from reference speech recorded by other speakers.

Expressive Speech Synthesis

Decentralized Policy Gradient for Nash Equilibria Learning of General-sum Stochastic Games

no code implementations14 Oct 2022 Yan Chen, Tao Li

For the case with exact pseudo gradients, we design a two-loop algorithm by the equivalence of Nash equilibrium and variational inequality problems.

On the Resilience of Traffic Networks under Non-Equilibrium Learning

no code implementations6 Oct 2022 Yunian Pan, Tao Li, Quanyan Zhu

We investigate the resilience of learning-based \textit{Intelligent Navigation Systems} (INS) to informational flow attacks, which exploit the vulnerabilities of IT infrastructure and manipulate traffic condition data.

MUG: Interactive Multimodal Grounding on User Interfaces

no code implementations29 Sep 2022 Tao Li, Gang Li, Jingjie Zheng, Purple Wang, Yang Li

To investigate the problem, we create a new dataset that consists of 77, 820 sequences of human user-agent interaction on mobile interfaces in which 20% involves multiple rounds of interactions.

Event-Triggered Extended State Observer Based Distributed Control of Nonlinear Vehicle Platoons

no code implementations16 Sep 2022 Anquan Liu, Tao Li, Yu Gu

Finally, we give the range of the control parameters to ensure the stability of the vehicle platoon system.

Sampling Attacks on Meta Reinforcement Learning: A Minimax Formulation and Complexity Analysis

1 code implementation29 Jul 2022 Tao Li, Haozhe Lei, Quanyan Zhu

It leads to two online attack schemes: Intermittent Attack and Persistent Attack, which enable the attacker to learn an optimal sampling attack, defined by an $\epsilon$-first-order stationary point, within $\mathcal{O}(\epsilon^{-2})$ iterations.

Meta-Learning Meta Reinforcement Learning +2

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

3 code implementations9 Jun 2022 Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew Dai, Andrew La, Andrew Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakaş, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartłomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, César Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodola, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, Francois Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocoń, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, Jose Hernandez-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras-Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Şenel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, Maria Jose Ramírez Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Orduna Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael Ivanitskiy, Michael Starritt, Michael Strube, Michał Swędrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T, Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha S. Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Miłkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima, Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, ZiRui Wang, Ziyi Wu

BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.

Common Sense Reasoning Math +1

Decentralized Online Regularized Learning Over Random Time-Varying Graphs

no code implementations7 Jun 2022 Xiwei Zhang, Tao Li, Xiaozheng Fu

We study the decentralized online regularized linear regression algorithm over random time-varying graphs.


Progressive Multi-scale Consistent Network for Multi-class Fundus Lesion Segmentation

2 code implementations31 May 2022 Along He, Kai Wang, Tao Li, Wang Bo, Hong Kang, Huazhu Fu

The two proposed PFF and DAB blocks can be integrated with the off-the-shelf backbone networks to address the two issues of multi-scale and feature inconsistency in the multi-class segmentation of fundus lesions, which will produce better feature representation in the feature space.

Lesion Segmentation Segmentation +1

Hilbert Curve Projection Distance for Distribution Comparison

1 code implementation30 May 2022 Tao Li, Cheng Meng, Hongteng Xu, Jun Yu

Distribution comparison plays a central role in many machine learning tasks like data classification and generative modeling.

Trainable Weight Averaging: A General Approach for Subspace Training

1 code implementation26 May 2022 Tao Li, Zhehao Huang, Yingwen Wu, Zhengbao He, Qinghua Tao, Xiaolin Huang, Chih-Jen Lin

Training deep neural networks (DNNs) in low-dimensional subspaces is a promising direction for achieving efficient training and better generalization performance.

Dimensionality Reduction Efficient Neural Network +3

Multi-speaker Multi-style Text-to-speech Synthesis With Single-speaker Single-style Training Data Scenarios

no code implementations23 Dec 2021 Qicong Xie, Tao Li, Xinsheng Wang, Zhichao Wang, Lei Xie, Guoqiao Yu, Guanglu Wan

Moreover, the explicit prosody features used in the prosody predicting module can increase the diversity of synthetic speech by adjusting the value of prosody features.

Speech Synthesis Style Transfer +1

M2DGR: A Multi-sensor and Multi-scenario SLAM Dataset for Ground Robots

2 code implementations19 Dec 2021 Jie Yin, Ang Li, Tao Li, Wenxian Yu, Danping Zou

We introduce M2DGR: a novel large-scale dataset collected by a ground robot with a full sensor-suite including six fish-eye and one sky-pointing RGB cameras, an infrared camera, an event camera, a Visual-Inertial Sensor (VI-sensor), an inertial measurement unit (IMU), a LiDAR, a consumer-grade Global Navigation Satellite System (GNSS) receiver and a GNSS-IMU navigation system with real-time kinematic (RTK) signals.

Subspace Adversarial Training

1 code implementation CVPR 2022 Tao Li, Yingwen Wu, Sizhe Chen, Kun Fang, Xiaolin Huang

Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust.

One-shot Voice Conversion For Style Transfer Based On Speaker Adaptation

no code implementations24 Nov 2021 Zhichao Wang, Qicong Xie, Tao Li, Hongqiang Du, Lei Xie, Pengcheng Zhu, Mengxiao Bi

One-shot style transfer is a challenging task, since training on one utterance makes model extremely easy to over-fit to training data and causes low speaker similarity and lack of expressiveness.

Style Transfer Voice Conversion

Enriching Source Style Transfer in Recognition-Synthesis based Non-Parallel Voice Conversion

no code implementations16 Jun 2021 Zhichao Wang, Xinyong Zhou, Fengyu Yang, Tao Li, Hongqiang Du, Lei Xie, Wendong Gan, Haitao Chen, Hai Li

Specifically, prosodic features are used to explicit model prosody, while VAE and reference encoder are used to implicitly model prosody, which take Mel spectrum and bottleneck feature as input respectively.

Style Transfer Voice Conversion

The Confluence of Networks, Games and Learning

no code implementations17 May 2021 Tao Li, Guanze Peng, Quanyan Zhu, Tamer Basar

In addition to existing research works on game-theoretic learning over networks, we highlight several new angles and research endeavors on learning in games that are related to recent developments in artificial intelligence.

Decision Making Management

DeepBlur: A Simple and Effective Method for Natural Image Obfuscation

no code implementations31 Mar 2021 Tao Li, Min Soo Choi

There is a growing privacy concern due to the popularity of social media and surveillance systems, along with advances in face recognition software.

Face Recognition

Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces

1 code implementation20 Mar 2021 Tao Li, Lei Tan, Qinghua Tao, Yipeng Liu, Xiaolin Huang

Deep neural networks (DNNs) usually contain massive parameters, but there is redundancy such that it is guessed that the DNNs could be trained in low-dimensional subspaces.

Dimensionality Reduction

Differentially Private Imaging via Latent Space Manipulation

no code implementations8 Mar 2021 Tao Li, Chris Clifton

There is growing concern about image privacy due to the popularity of social media and photo devices, along with increasing use of face recognition systems.

De-identification Face Recognition

Strongly Connected Topology Model and Confirmation-based Propagation Method for Cross-chain Interaction

no code implementations18 Feb 2021 Hong Su, Bing Guo, Yan Shen, Tao Li

Meanwhile, different from legacy networks, the propagation method is required to keep the data validity.

Distributed, Parallel, and Cluster Computing

Signal identification with Kalman Filter towards background-free neutrinoless double beta decay searches in gaseous detectors

no code implementations16 Feb 2021 Tao Li, Shaobo Wang, Yu Chen, Ke Han, Heng Lin, Kaixiang Ni, Wei Wang, Yiliu Xu, Anni Zou

Particle tracks and differential energy loss measured in high pressure gaseous detectors can be exploited for event identification in neutrinoless double beta decay~($0\nu \beta \beta$) searches.

Instrumentation and Detectors High Energy Physics - Experiment

A Benchmark of Ocular Disease Intelligent Recognition: One Shot for Multi-disease Detection

no code implementations16 Feb 2021 Ning li, Tao Li, Chunyu Hu, Kai Wang, Hong Kang

In ophthalmology, early fundus screening is an economic and effective way to prevent blindness caused by ophthalmic diseases.

Applications of Deep Learning in Fundus Images: A Review

1 code implementation25 Jan 2021 Tao Li, Wang Bo, Chunyu Hu, Hong Kang, Hanruo Liu, Kai Wang, Huazhu Fu

The use of fundus images for the early screening of eye diseases is of great clinical importance.

Image Generation Lesion Segmentation +1

Blackwell Online Learning for Markov Decision Processes

no code implementations28 Dec 2020 Tao Li, Guanze Peng, Quanyan Zhu

This work provides a novel interpretation of Markov Decision Processes (MDP) from the online optimization viewpoint.

Learning Theory Q-Learning

Slow Control System for PandaX-III experiment

no code implementations24 Dec 2020 Xiyu Yan, Xun Chen, Yu Chen, Bo Dai, Heng Lin, Tao Li, Ke Han, Kaixiang Ni, Fusang Wang, Shaobo Wang, Qibin Zheng, Xinning Zeng

The PandaX-III experiment uses high pressure gaseous time projection chamber to search for the neutrinoless double beta decay of $^{136}$Xe.

Anomaly Detection High Energy Physics - Experiment Instrumentation and Detectors

Locally-Aware Constrained Games on Networks

no code implementations19 Nov 2020 Guanze Peng, Tao Li, Shutian Liu, Juntao Chen, Quanyan Zhu

We use \textit{awareness levels} to capture the scope of the network constraints that players are aware of.

An Empirical-cum-Statistical Approach to Power-Performance Characterization of Concurrent GPU Kernels

no code implementations4 Nov 2020 Nilanjan Goswami, Amer Qouneh, Chao Li, Tao Li

Growing deployment of power and energy efficient throughput accelerators (GPU) in data centers demands enhancement of power-performance co-optimization capabilities of GPUs.

Distributed, Parallel, and Cluster Computing Hardware Architecture Graphics

Learning Causal Semantic Representation for Out-of-Distribution Prediction

1 code implementation NeurIPS 2021 Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu

Conventional supervised learning methods, especially deep ones, are found to be sensitive to out-of-distribution (OOD) examples, largely because the learned representation mixes the semantic factor with the variation factor due to their domain-specific correlation, while only the semantic factor causes the output.

Domain Adaptation

Towards Robust Neural Networks via Orthogonal Diversity

2 code implementations23 Oct 2020 Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Jia Cai, Feipeng Cai, Xiaolin Huang, Jie Yang

In this way, the proposed DIO augments the model and enhances the robustness of DNN itself as the learned features can be corrected by these mutually-orthogonal paths.

Adversarial Robustness Data Augmentation

UnQovering Stereotyping Biases via Underspecified Questions

1 code implementation Findings of the Association for Computational Linguistics 2020 Tao Li, Tushar Khot, Daniel Khashabi, Ashish Sabharwal, Vivek Srikumar

Our broad study reveals that (1) all these models, with and without fine-tuning, have notable stereotyping biases in these classes; (2) larger models often have higher bias; and (3) the effect of fine-tuning on bias varies strongly with the dataset and the model size.

Question Answering

Learn Robust Features via Orthogonal Multi-Path

no code implementations28 Sep 2020 Kun Fang, Xiaolin Huang, Yingwen Wu, Tao Li, Jie Yang

To defend adversarial attacks, we design a block containing multiple paths to learn robust features and the parameters of these paths are required to be orthogonal with each other.

On Data Augmentation for Extreme Multi-label Classification

no code implementations22 Sep 2020 Danqing Zhang, Tao Li, Haiyang Zhang, Bing Yin

Our contributions are two-factored: (1) we introduce a new state-of-the-art classifier that uses label attention with RoBERTa and combine it with our augmentation framework for further improvement; (2) we present a broad study on how effective are different augmentation methods in the XMC task.

Classification Data Augmentation +2

Attention-SLAM: A Visual Monocular SLAM Learning from Human Gaze

1 code implementation15 Sep 2020 Jinquan Li, Ling Pei, Danping Zou, Songpengcheng Xia, Qi Wu, Tao Li, Zhen Sun, Wenxian Yu

This paper proposes a novel simultaneous localization and mapping (SLAM) approach, namely Attention-SLAM, which simulates human navigation mode by combining a visual saliency model (SalNavNet) with traditional monocular visual SLAM.

Simultaneous Localization and Mapping

Distributed Stochastic Optimization With Unbounded Subgradients Over Randomly Time-Varying Networks

no code implementations20 Aug 2020 Tao Li, Keli Fu, Yan Chen, Xiaozheng Fu, Alexander L. Fradkov

Motivated by distributed statistical learning over uncertain communication networks, we study distributed stochastic optimization by networked nodes to cooperatively minimize a sum of convex cost functions.

Stochastic Optimization

OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings

1 code implementation EMNLP 2021 Sunipa Dev, Tao Li, Jeff M. Phillips, Vivek Srikumar

Language representations are known to carry stereotypical biases and, as a result, lead to biased predictions in downstream tasks.

Word Embeddings

Real-time Universal Style Transfer on High-resolution Images via Zero-channel Pruning

no code implementations16 Jun 2020 Jie An, Tao Li, Hao-Zhi Huang, Li Shen, Xuan Wang, Yongyi Tang, Jinwen Ma, Wei Liu, Jiebo Luo

Extracting effective deep features to represent content and style information is the key to universal style transfer.

Style Transfer

VecQ: Minimal Loss DNN Model Compression With Vectorized Weight Quantization

1 code implementation18 May 2020 Cheng Gong, Yao Chen, Ye Lu, Tao Li, Cong Hao, Deming Chen

Quantization has been proven to be an effective method for reducing the computing and/or storage cost of DNNs.

Model Compression object-detection +2

AN-GCN: An Anonymous Graph Convolutional Network Defense Against Edge-Perturbing Attack

no code implementations6 May 2020 Ao Liu, Beibei Li, Tao Li, Pan Zhou, Rui Wang

In this paper, we first generalize the formulation of edge-perturbing attacks and strictly prove the vulnerability of GCNs to such attacks in node classification tasks.

Adversarial Attack Classification +4

Structured Tuning for Semantic Role Labeling

1 code implementation ACL 2020 Tao Li, Parth Anand Jawale, Martha Palmer, Vivek Srikumar

We start with a strong baseline (RoBERTa) to validate the impact of our approach, and show that our framework outperforms the baseline by learning to comply with declarative constraints.

Semantic Role Labeling

Cooperative Extended State Observer Based Control of Vehicle Platoons With Arbitrarily Small Time Headway

no code implementations21 Apr 2020 Anquan Liu, Tao Li, Yu Gu, Haohui Dai

By using the stability theory of perturbed linear systems, we show that the control parameters can be properly designed to ensure the closed-loop and L2 string stabilities for any given positive time headway.

Self-Learning with Rectification Strategy for Human Parsing

no code implementations CVPR 2020 Tao Li, Zhiyuan Liang, Sanyuan Zhao, Jiahao Gong, Jianbing Shen

For the global error, we first transform category-wise features into a high-level graph model with coarse-grained structural information, and then decouple the high-level graph to reconstruct the category features.

Human Parsing Self-Learning

SFE-GACN: A Novel Unknown Attack Detection Method Using Intra Categories Generation in Embedding Space

no code implementations12 Apr 2020 Ao Liu, Yunpeng Wang, Tao Li

In this paper, we propose a novel unknown attack detection method based on Intra Categories Generation in Embedding Space, namely SFE-GACN, which might be the solution of few-shot problem.

Data Augmentation Generative Adversarial Network +1

A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors

no code implementations4 Mar 2020 Fanyi Xiao, Ling Pei, Lei Chu, Danping Zou, Wenxian Yu, Yifan Zhu, Tao Li

The experimental results show that the proposed method can surprisingly converge in a few iterations and achieve an accuracy of 91. 15% on a real IMU dataset, demonstrating the efficiency and effectiveness of the proposed method.

Human Activity Recognition Transfer Learning

Phylogenetic Study of 2019-nCoV by Using Alignment Free Method (Evolutionary Bifurcation of Novel Coronavirus Mutants)

no code implementations3 Mar 2020 Yang Gao, Tao Li, Liaofu Luo

It is found that there exist three types of virus mutations, namely, the mutation among sub-branches of the same branch, the off-root mutation and the root-oriented mutation between large branches of the tree.

Mutually unbiased measurement based entanglement witnesses

no code implementations4 Dec 2019 Tao Li, Le-Min Lai, Shao-Ming Fei, Zhi-Xi Wang

We study entanglement witness and present a construction of entanglement witnesses in terms of the mutually unbiased measurements (MUMs).

Quantum Physics

Component Attention Guided Face Super-Resolution Network: CAGFace

1 code implementation19 Oct 2019 Ratheesh Kalarot, Tao Li, Fatih Porikli

To make the best use of the underlying structure of faces, the collective information through face datasets and the intermediate estimates during the upsampling process, here we introduce a fully convolutional multi-stage neural network for 4$\times$ super-resolution for face images.


A Logic-Driven Framework for Consistency of Neural Models

1 code implementation IJCNLP 2019 Tao Li, Vivek Gupta, Maitrey Mehta, Vivek Srikumar

While neural models show remarkable accuracy on individual predictions, their internal beliefs can be inconsistent across examples.

Natural Language Inference

On Measuring and Mitigating Biased Inferences of Word Embeddings

2 code implementations25 Aug 2019 Sunipa Dev, Tao Li, Jeff Phillips, Vivek Srikumar

Word embeddings carry stereotypical connotations from the text they are trained on, which can lead to invalid inferences in downstream models that rely on them.

Natural Language Inference Word Embeddings

On Convergence Rate of Adaptive Multiscale Value Function Approximation For Reinforcement Learning

no code implementations22 Aug 2019 Tao Li, Quanyan Zhu

In this paper, we propose a generic framework for devising an adaptive approximation scheme for value function approximation in reinforcement learning, which introduces multiscale approximation.

reinforcement-learning Reinforcement Learning (RL)

Decentralized Cooperative Online Estimation With Random Observation Matrices, Communication Graphs and Time Delays

no code implementations22 Aug 2019 Jiexiang Wang, Tao Li, Xiwei Zhang

Firstly, for the delay-free case, we show that the algorithm gains can be designed properly such that all nodes' estimates converge to the true parameter in mean square and almost surely if the observation matrices and communication graphs satisfy the stochastic spatiotemporal persistence of excitation condition.

A Pvalue-guided Anomaly Detection Approach Combining Multiple Heterogeneous Log Parser Algorithms on IIoT Systems

no code implementations5 Jul 2019 Xueshuo Xie, Zhi Wang, Xuhang Xiao, Lei Yang, Shenwei Huang, Tao Li

In this paper, we use blockchain to prevent logs from being tampered with and propose a pvalue-guided anomaly detection approach.

Cryptography and Security

Augmenting Neural Networks with First-order Logic

1 code implementation ACL 2019 Tao Li, Vivek Srikumar

Today, the dominant paradigm for training neural networks involves minimizing task loss on a large dataset.

Chunking Natural Language Inference +3

Beauty Learning and Counterfactual Inference

no code implementations24 Apr 2019 Tao Li

This work showcases a new approach for causal discovery by leveraging user experiments and recent advances in photo-realistic image editing, demonstrating a potential of identifying causal factors and understanding complex systems counterfactually.

Causal Discovery counterfactual +1

T-SVD Based Non-convex Tensor Completion and Robust Principal Component Analysis

no code implementations23 Apr 2019 Tao Li, Jinwen Ma

Tensor completion and robust principal component analysis have been widely used in machine learning while the key problem relies on the minimization of a tensor rank that is very challenging.

Denoising Image Inpainting

BLVD: Building A Large-scale 5D Semantics Benchmark for Autonomous Driving

1 code implementation15 Mar 2019 Jianru Xue, Jianwu Fang, Tao Li, Bohua Zhang, Pu Zhang, Zhen Ye, Jian Dou

Instead, BLVD aims to provide a platform for the tasks of dynamic 4D (3D+temporal) tracking, 5D (4D+interactive) interactive event recognition and intention prediction.

Autonomous Driving Instance Segmentation +5

Understanding Beauty via Deep Facial Features

no code implementations30 Jan 2019 Xudong Liu, Tao Li, Hao Peng, Iris Chuoying Ouyang, Taehwan Kim, Ruizhe Wang

The concept of beauty has been debated by philosophers and psychologists for centuries, but most definitions are subjective and metaphysical, and deficit in accuracy, generality, and scalability.

Generative Adversarial Network

Student's t-Generative Adversarial Networks

no code implementations6 Nov 2018 Jinxuan Sun, Guoqiang Zhong, Yang Chen, Yongbin Liu, Tao Li, Zhongwen Guo

We propose a new method referring to conditional GAN, which equipments the latent noise with mixture of Student's t-distribution with attention mechanism in addition to class information.

Image Generation

Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension

no code implementations EMNLP 2018 Shusen Liu, Tao Li, Zhimin Li, Vivek Srikumar, Valerio Pascucci, Peer-Timo Bremer

Neural networks models have gained unprecedented popularity in natural language processing due to their state-of-the-art performance and the flexible end-to-end training scheme.

Decision Making Natural Language Inference +1

Structure Learning of Deep Networks via DNA Computing Algorithm

no code implementations25 Oct 2018 Guoqiang Zhong, Tao Li, Wenxue Liu, Yang Chen

The indicates that: 1) Using DNA computing algorithm to learn deep architectures is feasible; 2) Local minima should not be a problem of deep networks; 3) We can use early stop to kill the models with the bad performance just after several runs of training.

GPU based Parallel Optimization for Real Time Panoramic Video Stitching

no code implementations4 Oct 2018 Chengyao Du, Jingling Yuan, Jiansheng Dong, Lin Li, Mincheng Chen, Tao Li

In order to solve these problems, we propose a real-time panoramic video stitching framework. The framework we propose mainly consists of three algorithms, LORB image feature extraction algorithm, feature point matching algorithm based on LSH and GPU parallel video stitching algorithm based on CUDA. The experiment results show that the algorithm mentioned can improve the performance in the stages of feature extraction of images stitching and matching, the running speed of which is 11 times than that of the traditional ORB algorithm and 639 times than that of the traditional SIFT algorithm.

Image Stitching

Semi-supervised Text Regression with Conditional Generative Adversarial Networks

no code implementations2 Oct 2018 Tao Li, Xudong Liu, Shih-An Su

Enormous online textual information provides intriguing opportunities for understandings of social and economic semantics.

Generative Adversarial Network regression

YouTube AV 50K: An Annotated Corpus for Comments in Autonomous Vehicles

1 code implementation30 Jul 2018 Tao Li, Lei Lin, Minsoo Choi, Kaiming Fu, Siyuan Gong, Jian Wang

With one billion monthly viewers, and millions of users discussing and sharing opinions, comments below YouTube videos are rich sources of data for opinion mining and sentiment analysis.

Opinion Mining Self-Driving Cars +1

Aspect Based Sentiment Analysis with Gated Convolutional Networks

1 code implementation ACL 2018 Wei Xue, Tao Li

Aspect based sentiment analysis (ABSA) can provide more detailed information than general sentiment analysis, because it aims to predict the sentiment polarities of the given aspects or entities in text.

Aspect-Based Sentiment Analysis Aspect Category Sentiment Analysis

Collaborative Filtering with Topic and Social Latent Factors Incorporating Implicit Feedback

no code implementations26 Mar 2018 Guang-Neng Hu, Xin-yu Dai, Feng-Yu Qiu, Rui Xia, Tao Li, Shu-Jian Huang, Jia-Jun Chen

First, we propose a novel model {\em \mbox{MR3}} to jointly model three sources of information (i. e., ratings, item reviews, and social relations) effectively for rating prediction by aligning the latent factors and hidden topics.

Collaborative Filtering Recommendation Systems

BTS-DSN: Deeply Supervised Neural Network with Short Connections for Retinal Vessel Segmentation

1 code implementation11 Mar 2018 Song Guo, Kai Wang, Hong Kang, Yujun Zhang, Yingqi Gao, Tao Li

Results: The proposed BTS-DSN has been verified on DRIVE, STARE and CHASE_DB1 datasets, and showed competitive performance over other state-of-the-art methods.

Retinal Vessel Segmentation Segmentation +1

A Class-Incremental Learning Method Based on One Class Support Vector Machine

no code implementations1 Mar 2018 Chengfei Yao, Jie Zou, Yanan Luo, Tao Li, Gang Bai

Then the support vectors of the old classes and the support vectors of the new class are reused to train 1VS1 classifiers for the confuse part.

Class Incremental Learning Incremental Learning

HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image

2 code implementations28 Feb 2018 Yanan Luo, Jie Zou, Chengfei Yao, Tao Li, Gang Bai

In this paper, we propose a novel convolutional neural network framework for the characteristics of hyperspectral image data, called HSI-CNN.

Classification General Classification +1

MTNA: A Neural Multi-task Model for Aspect Category Classification and Aspect Term Extraction On Restaurant Reviews

no code implementations IJCNLP 2017 Wei Xue, Wubai Zhou, Tao Li, Qing Wang

Online reviews are valuable resources not only for consumers to make decisions before purchase, but also for providers to get feedbacks for their services or commodities.

Aspect-Based Sentiment Analysis Extract Aspect +5

Online Interactive Collaborative Filtering Using Multi-Armed Bandit with Dependent Arms

no code implementations10 Aug 2017 Qing Wang, Chunqiu Zeng, Wubai Zhou, Tao Li, Larisa Shwartz, Genady Ya. Grabarnik

To address these issues, collaborative filtering (CF), one of the recommendation techniques relying on the interaction data only, as well as the online multi-armed bandit mechanisms, capable of achieving the balance between exploitation and exploration, are adopted in the online interactive recommendation settings, by assuming independent items (i. e., arms).

Collaborative Filtering Recommendation Systems

Structure-measure: A New Way to Evaluate Foreground Maps

1 code implementation ICCV 2017 Deng-Ping Fan, Ming-Ming Cheng, Yun Liu, Tao Li, Ali Borji

Our new measure simultaneously evaluates region-aware and object-aware structural similarity between a SM and a GT map.

Object object-detection +5

Lesion detection and Grading of Diabetic Retinopathy via Two-stages Deep Convolutional Neural Networks

no code implementations2 May 2017 Yehui Yang, Tao Li, Wensi Li, Haishan Wu, Wei Fan, Wensheng Zhang

We propose an automatic diabetic retinopathy (DR) analysis algorithm based on two-stages deep convolutional neural networks (DCNN).

Lesion Detection

Z$_{2}$ spin liquid phase on the kagome lattice: a new saddle point

no code implementations9 Jan 2016 Tao Li

The Z$_{2}$ state is found to be slightly more stable than the extensively studied U(1) gapless Dirac spin liquid state in both the $J_{2}\neq0$ and the $J_{2}=0$ case and to possess a small spinon gap for $J_{2}<0. 2$.

Strongly Correlated Electrons

Skopus: Mining top-k sequential patterns under leverage

1 code implementation26 Jun 2015 Francois Petitjean, Tao Li, Nikolaj Tatti, Geoffrey I. Webb

It combines (1) a novel definition of the expected support for a sequential pattern - a concept on which most interestingness measures directly rely - with (2) SkOPUS: a new branch-and-bound algorithm for the exact discovery of top-k sequential patterns under a given measure of interest.

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