Papers
Learning-Rate-Free Learning by D-Adaptation
Aaron Defazio, Konstantin Mishchenko
Learning Rate Schedules in the Presence of Distribution Shift
Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni et al.
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation
Fengxue Zhang, Jialin Song, James C Bowden et al.
Learning Representations without Compositional Assumptions
Tennison Liu, Jeroen Berrevoets, Zhaozhi Qian et al.
Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping
Baorui Ma, Yu-Shen Liu, Zhizhong Han
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design
Zaixi Zhang, Qi Liu
Learning Temporally AbstractWorld Models without Online Experimentation
Benjamin Freed, Siddarth Venkatraman, Guillaume Adrien Sartoretti et al.
Learning the Dynamics of Sparsely Observed Interacting Systems
Linus Bleistein, Adeline Fermanian, Anne-Sophie Jannot et al.
Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs
Sara Venturini, Andrea Cristofari, Francesco Rinaldi et al.
Learning to Bid in Repeated First-Price Auctions with Budgets
Qian Wang, Zongjun Yang, Xiaotie Deng et al.
Learning to Boost Training by Periodic Nowcasting Near Future Weights
Jinhyeok Jang, Woo-Han Yun, Won Hwa Kim et al.
Learning to Decouple Complex Systems
Zihan Zhou, Tianshu Yu
Learning to Design Analog Circuits to Meet Threshold Specifications
Dmitrii Krylov, Pooya Khajeh, Junhan Ouyang et al.
Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model
Siyu Chen, Jibang Wu, Yifan Wu et al.
Learning to Initiate and Reason in Event-Driven Cascading Processes
Yuval Atzmon, Eli Meirom, Shie Mannor et al.
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling
Tianqi Chen, Mingyuan Zhou
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
Zixuan Hu, Li Shen, Zhenyi Wang et al.
Learning to Maximize Mutual Information for Dynamic Feature Selection
Ian Connick Covert, Wei Qiu, Mingyu Lu et al.
Learning to Optimize Differentiable Games
Xuxi Chen, Nelson Vadori, Tianlong Chen et al.
Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement
Eden Saig, Nir Rosenfeld
Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator
Sicheng Zhu, Bang An, Furong Huang et al.
Learning Unnormalized Statistical Models via Compositional Optimization
Wei Jiang, Jiayu Qin, Lingyu Wu et al.
Learning useful representations for shifting tasks and distributions
Jianyu Zhang, Leon Bottou
Learn to Accumulate Evidence from All Training Samples: Theory and Practice
Deep Shankar Pandey, Qi Yu