ICLR

Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning

Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu

Comments Accepted as a conference paper at ICLR 2023

Neural-based classification rule learning for sequential data

Marine Collery, Philippe Bonnard, François Fages, Remy Kusters

Comments Published as a conference paper at ICLR 2023

Energy-Based Test Sample Adaptation for Domain Generalization

Zehao Xiao, Xiantong Zhen, Shengcai Liao, Cees G. M. Snoek

Comments Accepted by ICLR 2023

Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks

Bowen Jin, Yu Zhang, Yu Meng, Jiawei Han

Comments ICLR 2023. (Code: https://github.com/PeterGriffinJin/Edgeformers)

Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model

Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou

Comments ICLR 2023

EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model

Yifu Yuan, Jianye Hao, Fei Ni, Yao Mu, Yan Zheng, Yujing Hu, Jinyi Liu, Yingfeng Chen, Changjie Fan

Comments Published as a conference paper at ICLR 2023

Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes

Zecheng Hao, Jianhao Ding, Tong Bu, Tiejun Huang, Zhaofei Yu

Comments Accepted by ICLR 2023

Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems

Yihao Feng, Shentao Yang, Shujian Zhang, Jianguo Zhang, Caiming Xiong, Mingyuan Zhou, Huan Wang

Comments Published as a conference paper at ICLR 2023

Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation

Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock, Samuel L Smith, Yee Whye Teh

Comments ICLR 2023

SimPer: Simple Self-Supervised Learning of Periodic Targets

Yuzhe Yang, Xin Liu, Jiang Wu, Silviu Borac, Dina Katabi, Ming-Zher Poh, Daniel McDuff

Comments ICLR 2023 Oral (notable top 5%)

Robust Fair Clustering: A Novel Fairness Attack and Defense Framework

Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu

Comments Accepted to the 11th International Conference on Learning Representations (ICLR 2023)

Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies

Rui Yuan, Simon S. Du, Robert M. Gower, Alessandro Lazaric, Lin Xiao

Comments This version adds a table of comparison for the literature review. The paper is published as a conference paper at ICLR 2023

Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation

Maksym Yatsura, Kaspar Sakmann, N. Grace Hua, Matthias Hein, Jan Hendrik Metzen

Comments accepted at ICLR 2023

Understanding new tasks through the lens of training data via exponential tilting

Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

Comments Accepted in ICLR 2023

QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization

Xiuying Wei, Ruihao Gong, Yuhang Li, Xianglong Liu, Fengwei Yu

Comments Accepted by ICLR 2022

Diversify and Disambiguate: Learning From Underspecified Data

Yoonho Lee, Huaxiu Yao, Chelsea Finn

Comments ICLR 2023. Code is available at https://github.com/yoonholee/DivDis

Improving Deep Policy Gradients with Value Function Search

Enrico Marchesini, Christopher Amato

Comments Accepted at The Eleventh International Conference on Learning Representations (ICLR)

Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth Estimation

Peizhe Jiang, Wei Yang, Xiaoqing Ye, Xiao Tan, Meng Wu

Comments Accepted by ICLR and IEEE Robotics and Automation Letters (RAL)

Journal ref IEEE Robotics and Automation Letters 7.4 (2022): 12094-12101

Learning Language Representations with Logical Inductive Bias

Jianshu Chen

Comments Published as a conference paper at ICLR 2023

Outcome-directed Reinforcement Learning by Uncertainty & Temporal Distance-Aware Curriculum Goal Generation

Daesol Cho, Seungjae Lee, H. Jin Kim

Comments ICLR 2023 Spotlight. First two authors contributed equally

Dense RGB SLAM with Neural Implicit Maps

Heng Li, Xiaodong Gu, Weihao Yuan, Luwei Yang, Zilong Dong, Ping Tan

Comments Accepted by ICLR 2023; Camera-Ready Version; The code is at poptree.github.io/DIM-SLAM

SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization

Hanseul Cho, Chulhee Yun

Comments ICLR 2023 camera-ready version; 46 pages

MEDFAIR: Benchmarking Fairness for Medical Imaging

Yongshuo Zong, Yongxin Yang, Timothy Hospedales

Comments Accepted to ICLR 2023

DocPrompting: Generating Code by Retrieving the Docs

Shuyan Zhou, Uri Alon, Frank F. Xu, Zhiruo Wang, Zhengbao Jiang, Graham Neubig

Comments ICLR 2023 (notable-top-25%); code and data are available at https://github.com/shuyanzhou/docprompting

Causal Balancing for Domain Generalization

Xinyi Wang, Michael Saxon, Jiachen Li, Hongyang Zhang, Kun Zhang, William Yang Wang

Comments Published at ICLR 2023

Large-Scale Representation Learning on Graphs via Bootstrapping

Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rémi Munos, Petar Veličković, Michal Valko

Comments Published as a conference paper at ICLR 2022

Learnable Topological Features for Phylogenetic Inference via Graph Neural Networks

Cheng Zhang

Comments ICLR 2023

Stable Target Field for Reduced Variance Score Estimation in Diffusion Models

Yilun Xu, Shangyuan Tong, Tommi Jaakkola

Comments Accepted by ICLR 2023. Code available at: https://github.com/Newbeeer/stf

H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection

Xue Yang, Gefan Zhang, Wentong Li, Xuehui Wang, Yue Zhou, Junchi Yan

Comments 15 pages, 6 figures, 8 tables, accepted by ICLR 2023, the source code is available at https://github.com/yangxue0827/h2rbox-mmrotate and https://github.com/yangxue0827/h2rbox-jittor

The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks

Daniel Kunin, Atsushi Yamamura, Chao Ma, Surya Ganguli

Comments 41 pages, 5 figures, ICLR 2023