no code implementations • ECCV 2020 • Tianyi Zhang, Guosheng Lin, Weide Liu, Jianfei Cai, Alex Kot
Finally, by training the segmentation model with the masks generated by our Splitting vs Merging strategy, we achieve the state-of-the-art weakly-supervised segmentation results on the Pascal VOC 2012 benchmark.
Weakly supervised segmentation
Weakly-Supervised Semantic Segmentation
no code implementations • 7 Jun 2022 • Tianyi Zhang, Youdan Feng, Yunlu Feng, Guanglei Zhang
Computer-aided diagnosis (CAD) using the deep learning method has the potential to solve the problem of insufficient pathology staffing.
1 code implementation • 2 Jun 2022 • Binhang Yuan, Yongjun He, Jared Quincy Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Re, Ce Zhang
Our key technical contribution is a scheduling algorithm that allocates different computational "tasklets" in the training of foundation models to a group of decentralized GPU devices connected by a slow heterogeneous network.
no code implementations • 23 May 2022 • Tianyi Zhang, Mina Lee, Lisa Li, Ende Shen, Tatsunori B. Hashimoto
While pretrained language models (PLMs) have greatly improved text generation, they have also been known to produce unfaithful or inappropriate content.
no code implementations • 14 Feb 2022 • Yi Jiang, Tianyi Zhang, Wei zhang
Owing to the same layered form as an ANN, a MNN can also be optimized using the back-propagation (BP) algorithm.
1 code implementation • 27 Dec 2021 • Tianyi Zhang, Yunlu Feng, Yu Zhao, Guangda Fan, Aiming Yang, Shangqin Lyu, Peng Zhang, Fan Song, Chenbin Ma, Yangyang Sun, Youdan Feng, Guanglei Zhang
Pancreatic cancer is one of the most malignant cancers in the world, which deteriorates rapidly with very high mortality.
no code implementations • 19 Dec 2021 • Nan Lu, Tianyi Zhang, Tongtong Fang, Takeshi Teshima, Masashi Sugiyama
A key assumption in supervised learning is that training and test data follow the same probability distribution.
no code implementations • 10 Dec 2021 • Tianyi Zhang, Shirui Zhang, Ziwei Chen, Dianbo Liu
Federated machine learning is a versatile and flexible tool to utilize distributed data from different sources, especially when communication technology develops rapidly and an unprecedented amount of data could be collected on mobile devices nowadays.
1 code implementation • 9 Sep 2021 • Tianyi Zhang, Matthew Johnson-Roberson
Robot localization remains a challenging task in GPS denied environments.
no code implementations • 16 Aug 2021 • Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Kohd, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, aditi raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang
AI is undergoing a paradigm shift with the rise of models (e. g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.
1 code implementation • 16 Jul 2021 • Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamas Sarlos, Adrian Weller, Thomas Weingarten
In this paper we provide, to the best of our knowledge, the first comprehensive approach for incorporating various masking mechanisms into Transformers architectures in a scalable way.
no code implementations • CVPR 2021 • Tianyi Zhang, Jie Lin, Peng Hu, Bin Zhao, Mohamed M. Sabry Aly
Unlike convolutions which are inherently parallel, the de-facto standard for NMS, namely GreedyNMS, cannot be easily parallelized and thus could be the performance bottleneck in convolutional object detection pipelines.
1 code implementation • NAACL 2021 • Tianyi Zhang, Tatsunori Hashimoto
We study how masking and predicting tokens in an unsupervised fashion can give rise to linguistic structures and downstream performance gains.
no code implementations • 21 Mar 2021 • Jiaying Ren, Tianyi Zhang, Jian Li, Petre Stoica
In a previous paper, a relaxation-based algorithm, referred to as 1bRELAX, has been proposed to iteratively maximize the likelihood function.
no code implementations • 19 Mar 2021 • Tianyi Zhang, Jiaying Ren, Jian Li, Lam H. Nguyen, Petre Stoica
Radio frequency interference (RFI) mitigation and radar echo recovery are critically important for the proper functioning of ultra-wideband (UWB) radar systems using one-bit sampling techniques.
no code implementations • 19 Feb 2021 • Daniel Russo, Assaf Zeevi, Tianyi Zhang
We consider a discounted infinite horizon optimal stopping problem.
no code implementations • 17 Feb 2021 • Tianyi Zhang, Jiaying Ren, Jian Li, Lam H. Nguyen, Petre Stoica
A one-bit UWB system obtains its signed measurements via a low-cost and high rate sampling scheme, referred to as the Continuous Time Binary Value (CTBV) technology.
no code implementations • 25 Jan 2021 • Lucas Lafeta, Aurea Corradi, Tianyi Zhang, Ethan Kahn, Ismail Bilgin, Bruno R. Carvalho, Swastik Kar, Mauricio Terrones, Leandro M. Malard
Semiconducting Transition Metal Dichalcogenides (TMDs) have significant nonlinear optical effects.
Mesoscale and Nanoscale Physics
1 code implementation • 7 Dec 2020 • Tianyi Zhang, Jiankun Wang, Max Q. -H. Meng
Sampling-based path planning is a popular methodology for robot path planning.
no code implementations • 18 Oct 2020 • Jianchao Lu, Xi Zheng, Tianyi Zhang, Michael Sheng, Chen Wang, Jiong Jin, Shui Yu, Wanlei Zhou
In this paper, we propose a novel driver fatigue detection method by embedding surface electromyography (sEMG) sensors on a steering wheel.
no code implementations • 22 Aug 2020 • Min Fu, Jiwei Guan, Xi Zheng, Jie zhou, Jianchao Lu, Tianyi Zhang, Shoujie Zhuo, Lijun Zhan, Jian Yang
Existing solution recommendation methods for online customer service are unable to determine the best solutions at runtime, leading to poor satisfaction of end customers.
no code implementations • 8 Aug 2020 • Dongbo Xi, Bowen Song, Fuzhen Zhuang, Yongchun Zhu, Shuai Chen, Tianyi Zhang, Yuan Qi, Qing He
In this paper, we propose the Dual Importance-aware Factorization Machines (DIFM), which exploits the internal field information among users' behavior sequence from dual perspectives, i. e., field value variations and field interactions simultaneously for fraud detection.
no code implementations • 8 Jul 2020 • Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama
A default assumption in many machine learning scenarios is that the training and test samples are drawn from the same probability distribution.
1 code implementation • ICLR 2021 • Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Q. Weinberger, Yoav Artzi
We empirically test the impact of these factors, and identify alternative practices that resolve the commonly observed instability of the process.
no code implementations • NeurIPS 2020 • Han Lin, Haoxian Chen, Tianyi Zhang, Clement Laroche, Krzysztof Choromanski
Orthogonal Monte Carlo (OMC) is a very effective sampling algorithm imposing structural geometric conditions (orthogonality) on samples for variance reduction.
no code implementations • 19 Mar 2020 • Tianyi Zhang, Yun Gu, Xiaolin Huang, Enmei Tu, Jie Yang
In particular, we incorporate a disparity-based constraint mechanism into the generation of SR images in a deep neural network framework with an additional atrous parallax-attention modules.
1 code implementation • 19 Feb 2020 • Tianyi Zhang, Shahrzad Shirzad, Bibek Wagle, Adrian S. Lemoine, Patrick Diehl, Hartmut Kaiser
This paper is a follow-up paper on the fundamental implementation of hpxMP, an implementation of the OpenMP standard which utilizes the C++ standard library for Parallelism and Concurrency (HPX) to schedule and manage tasks.
Distributed, Parallel, and Cluster Computing Programming Languages
1 code implementation • 6 Feb 2020 • Yao Deng, Xi Zheng, Tianyi Zhang, Chen Chen, Guannan Lou, Miryung Kim
We derive several implications for system and middleware builders: (1) when adding a defense component against adversarial attacks, it is important to deploy multiple defense methods in tandem to achieve a good coverage of various attacks, (2) a blackbox attack is much less effective compared with a white-box attack, implying that it is important to keep model details (e. g., model architecture, hyperparameters) confidential via model obfuscation, and (3) driving models with a complex architecture are preferred if computing resources permit as they are more resilient to adversarial attacks than simple models.
2 code implementations • NeurIPS 2020 • Geoff Pleiss, Tianyi Zhang, Ethan R. Elenberg, Kilian Q. Weinberger
Not all data in a typical training set help with generalization; some samples can be overly ambiguous or outrightly mislabeled.
no code implementations • 31 Dec 2019 • Lanfei Wang, Lingxi Xie, Tianyi Zhang, Jun Guo, Qi Tian
Neural Architecture Search (NAS) is an emerging topic in machine learning and computer vision.
no code implementations • 20 Oct 2019 • Nan Lu, Tianyi Zhang, Gang Niu, Masashi Sugiyama
The recently proposed unlabeled-unlabeled (UU) classification method allows us to train a binary classifier only from two unlabeled datasets with different class priors.
2 code implementations • 9 Oct 2019 • Tianyi Zhang, Zhiqiu Lin, Guandao Yang, Christopher De Sa
Low-precision training reduces computational cost and produces efficient models.
no code implementations • 25 Sep 2019 • Geoff Pleiss, Tianyi Zhang, Ethan R. Elenberg, Kilian Q. Weinberger
This paper introduces a new method to discover mislabeled training samples and to mitigate their impact on the training process of deep networks.
no code implementations • 14 May 2019 • Tianyi Zhang, Dengji Zhao, Wen Zhang, Xuming He
We consider a fixed-price mechanism design setting where a seller sells one item via a social network, but the seller can only directly communicate with her neighbours initially.
2 code implementations • 26 Apr 2019 • Guandao Yang, Tianyi Zhang, Polina Kirichenko, Junwen Bai, Andrew Gordon Wilson, Christopher De Sa
Low precision operations can provide scalability, memory savings, portability, and energy efficiency.
12 code implementations • ICLR 2020 • Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi
We propose BERTScore, an automatic evaluation metric for text generation.
1 code implementation • 7 Mar 2019 • Tianyi Zhang, Shahrzad Shirzad, Patrick Diehl, R. Tohid, Weile Wei, Hartmut Kaiser
Not only must users port their own codes, but often users rely on highly optimized libraries such as BLAS and LAPACK which use OpenMP for parallization.
Distributed, Parallel, and Cluster Computing
6 code implementations • 19 Feb 2019 • Felix Wu, Tianyi Zhang, Amauri Holanda de Souza Jr., Christopher Fifty, Tao Yu, Kilian Q. Weinberger
Graph Convolutional Networks (GCNs) and their variants have experienced significant attention and have become the de facto methods for learning graph representations.
Ranked #3 on
Text Classification
on 20NEWS
(using extra training data)
no code implementations • 29 Mar 2018 • Zhize Li, Tianyi Zhang, Shuyu Cheng, Jun Zhu, Jian Li
In this paper, we apply the variance reduction tricks on Hamiltonian Monte Carlo and achieve better theoretical convergence results compared with the variance-reduced Langevin dynamics.
no code implementations • 7 Mar 2018 • Tianyi Zhang, Guosheng Lin, Jianfei Cai, Tong Shen, Chunhua Shen, Alex C. Kot
In our work, we focus on the weakly supervised semantic segmentation with image label annotations.