ICLR Papers
6,124 papers found • Page 113 of 123
Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei et al.
Robust Similarity Learning with Difference Alignment Regularization
Shuo Chen, Gang Niu, Chen Gong et al.
Robust Training of Federated Models with Extremely Label Deficiency
Yonggang Zhang, Zhiqin Yang, Xinmei Tian et al.
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
Hao Cheng, Qingsong Wen, Yang Liu et al.
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs
Aakash Sunil Lahoti, Stefani Karp, Ezra Winston et al.
Rotation Has Two Sides: Evaluating Data Augmentation for Deep One-class Classification
Guodong Wang, Yunhong Wang, Xiuguo Bao et al.
RTFS-Net: Recurrent Time-Frequency Modelling for Efficient Audio-Visual Speech Separation
Samuel Pegg, Kai Li, Xiaolin Hu
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
Jiayuan Gu, Sean Kirmani, Paul Wohlhart et al.
S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic
Safa Messaoud, Billel Mokeddem, Zhenghai Xue et al.
Safe and Robust Watermark Injection with a Single OoD Image
Shuyang Yu, Junyuan Hong, Haobo Zhang et al.
Safe Collaborative Filtering
Riku Togashi, Tatsushi Oka, Naoto Ohsaka et al.
SafeDreamer: Safe Reinforcement Learning with World Models
Weidong Huang, Jiaming Ji, Chunhe Xia et al.
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
Yinan Zheng, Jianxiong Li, Dongjie Yu et al.
Safe RLHF: Safe Reinforcement Learning from Human Feedback
Juntao Dai, Xuehai Pan, Ruiyang Sun et al.
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions
Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio et al.
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation
Mucong Ding, Bang An, Yuancheng Xu et al.
SALMONN: Towards Generic Hearing Abilities for Large Language Models
Changli Tang, Wenyi Yu, Guangzhi Sun et al.
SALMON: Self-Alignment with Instructable Reward Models
Zhiqing Sun, Yikang Shen, Hongxin Zhang et al.
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
Chongyu Fan, Jiancheng Liu, Yihua Zhang et al.
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
Jianliang He, Han Zhong, Zhuoran Yang
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
Jiacheng Guo, Minshuo Chen, Huan Wang et al.
Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
Thomas T. Zhang, Leonardo Felipe Toso, James Anderson et al.
Sample-Efficient Multi-Agent RL: An Optimization Perspective
Nuoya Xiong, Zhihan Liu, Zhaoran Wang et al.
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
Ziping Xu, Zifan Xu, Runxuan Jiang et al.
Sample-Efficient Quality-Diversity by Cooperative Coevolution
Ke Xue, Ren-Jian Wang, Pengyi Li et al.
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
Frederic Koehler, Thuy-Duong Vuong
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya et al.
SaNN: Simple Yet Powerful Simplicial-aware Neural Networks
Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri
SaProt: Protein Language Modeling with Structure-aware Vocabulary
Jin Su, Chenchen Han, Yuyang Zhou et al.
SAS: Structured Activation Sparsification
Yusuke Sekikawa, Shingo Yashima
Scalable and Effective Implicit Graph Neural Networks on Large Graphs
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi et al.
Scalable Diffusion for Materials Generation
Sherry Yang, Kwanghwan Cho, Amil Merchant et al.
Scalable Language Model with Generalized Continual Learning
Bohao PENG, Zhuotao Tian, Shu Liu et al.
Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing
Minyang Hu, Hong Chang, Bingpeng Ma et al.
Scalable Monotonic Neural Networks
Hyunho Kim, Jong-Seok Lee
Scalable Neural Network Kernels
Arijit Sehanobish, Krzysztof Choromanski, YUNFAN ZHAO et al.
Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks
Khurram Javed, Haseeb Shah, Richard Sutton et al.
Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
Jijin Hu, Ke Li, Yonggang Qi et al.
ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models
Yingqing He, Shaoshu Yang, Haoxin Chen et al.
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation
Xin Li, Jing Yu Koh, Alexander Ku et al.
Scaling Convex Neural Networks with Burer-Monteiro Factorization
Arda Sahiner, Tolga Ergen, Batu Ozturkler et al.
Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement
Kai Xu, Rongyu Chen, Gianni Franchi et al.
Scaling Laws for Associative Memories
Vivien Cabannes, Elvis Dohmatob, Alberto Bietti
Scaling Laws for Sparsely-Connected Foundation Models
Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby et al.
Scaling Laws of RoPE-based Extrapolation
Xiaoran Liu, Hang Yan, Chenxin An et al.
Scaling physics-informed hard constraints with mixture-of-experts
Nithin Chalapathi, Yiheng Du, Aditi Krishnapriyan
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Chenxiang Ma, Jibin Wu, Chenyang Si et al.
SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos
Yulei Niu, Wenliang Guo, Long Chen et al.
Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions
Frank Cole, Yulong Lu