ICLR

RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data

Sangwoo Mo, Jong-Chyi Su, Chih-Yao Ma, Mido Assran, Ishan Misra, Licheng Yu, Sean Bell

Comments ICLR 2023

BrainBERT: Self-supervised representation learning for intracranial recordings

Christopher Wang, Vighnesh Subramaniam, Adam Uri Yaari, Gabriel Kreiman, Boris Katz, Ignacio Cases, Andrei Barbu

Comments 9 pages, 6 figures, ICLR 2023

Contextual bandits with concave rewards, and an application to fair ranking

Virginie Do, Elvis Dohmatob, Matteo Pirotta, Alessandro Lazaric, Nicolas Usunier

Comments ICLR 2023

Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules

Kazuki Irie, Jürgen Schmidhuber

Comments Accepted to ICLR 2023

Learning ReLU networks to high uniform accuracy is intractable

Julius Berner, Philipp Grohs, Felix Voigtlaender

Comments Accepted at ICLR 2023

Automated Data Augmentations for Graph Classification

Youzhi Luo, Michael McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

Comments Accepted by ICLR 2023

Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance

Xueyi Liu, Ji Zhang, Ruizhen Hu, Haibin Huang, He Wang, Li Yi

Comments ICLR 2023

Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations

Ziyu Jiang, Yinpeng Chen, Mengchen Liu, Dongdong Chen, Xiyang Dai, Lu Yuan, Zicheng Liu, Zhangyang Wang

Comments Accepted by ICLR 2023

Cross-Layer Retrospective Retrieving via Layer Attention

Yanwen Fang, Yuxi Cai, Jintai Chen, Jingyu Zhao, Guangjian Tian, Guodong Li

Comments Published as a conference paper at ICLR 2023

Improving Deep Regression with Ordinal Entropy

Shihao Zhang, Linlin Yang, Michael Bi Mi, Xiaoxu Zheng, Angela Yao

Comments Accepted to ICLR 2023. Project page: https://github.com/needylove/OrdinalEntropy

Behavior Prior Representation learning for Offline Reinforcement Learning

Hongyu Zang, Xin Li, Jie Yu, Chen Liu, Riashat Islam, Remi Tachet Des Combes, Romain Laroche

Comments ICLR 2023

Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences

Lin Guan, Karthik Valmeekam, Subbarao Kambhampati

Comments ICLR 2023 Camera Ready

FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

Kaiyuan Zhang, Guanhong Tao, Qiuling Xu, Siyuan Cheng, Shengwei An, Yingqi Liu, Shiwei Feng, Guangyu Shen, Pin-Yu Chen, Shiqing Ma, Xiangyu Zhang

Comments Accepted by ICLR 2023. Code is available at https://github.com/KaiyuanZh/FLIP

Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization

Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang

Comments ICLR'23, v3: update the acknowledgement and corresponding authors

Out-of-Distribution Representation Learning for Time Series Classification

Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, Xing Xie

Comments ICLR 2023 camera-ready version; code is at: https://github.com/microsoft/robustlearn

Agent-based Graph Neural Networks

Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer

Comments 32 pages, 6 figures, ICLR 2023

AANG: Automating Auxiliary Learning

Lucio M. Dery, Paul Michel, Mikhail Khodak, Graham Neubig, Ameet Talwalkar

Comments Accepted to ICLR 2023 22 pages, 7 tables and 5 figures

Understanding The Robustness of Self-supervised Learning Through Topic Modeling

Zeping Luo, Shiyou Wu, Cindy Weng, Mo Zhou, Rong Ge

Comments Accepted at ICLR 2023. Camera ready version

Systematic Rectification of Language Models via Dead-end Analysis

Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung, Samira Shabanian

Comments The Eleventh International Conference on Learning Representations, ICLR'23

Journal ref ICLR 2023

Dirichlet-based Uncertainty Calibration for Active Domain Adaptation

Mixue Xie, Shuang Li, Rui Zhang, Chi Harold Liu

Comments Accepted at ICLR 2023 as Spotlight

The Provable Benefits of Unsupervised Data Sharing for Offline Reinforcement Learning

Hao Hu, Yiqin Yang, Qianchuan Zhao, Chongjie Zhang

Comments Eleventh International Conference on Learning Representations (ICLR), 2023

Tailoring Language Generation Models under Total Variation Distance

Haozhe Ji, Pei Ke, Zhipeng Hu, Rongsheng Zhang, Minlie Huang

Comments Published in ICLR 2023 (notable-top-5%)

Journal ref International Conference on Learning Representations (ICLR 2023)

Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance

Yoonjeon Kim, Hyunsu Kim, Junho Kim, Yunjey Choi, Eunho Yang

Comments Accepted to ICLR 2023

A Unified Framework for Soft Threshold Pruning

Yanqi Chen, Zhengyu Ma, Wei Fang, Xiawu Zheng, Zhaofei Yu, Yonghong Tian

Comments To appear in the 11th International Conference on Learning Representations (ICLR 2023)

Modeling Multimodal Aleatoric Uncertainty in Segmentation with Mixture of Stochastic Experts

Zhitong Gao, Yucong Chen, Chuyu Zhang, Xuming He

Comments Published in ICLR 2023

Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation

Jun-Kun Wang, Andre Wibisono

Comments Accepted at ICLR (International Conference on Learning Representations), 2023

Disentanglement of Correlated Factors via Hausdorff Factorized Support

Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt

Comments Accepted to ICLR 2023

Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models

Meng Liu, Haoran Liu, Shuiwang Ji

Comments Accepted by ICLR 2023

Empowering Graph Representation Learning with Test-Time Graph Transformation

Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah

Comments ICLR 2023

Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning

Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V. Albrecht

Comments International Conference on Learning Representations (ICLR), 2023