Papers
ProTransformer: Robustify Transformers via Plug-and-Play Paradigm
Zhichao Hou, Weizhi Gao, Yuchen Shen et al.
Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks
Zhenghao Xu, Yuqing Wang, Tuo Zhao et al.
Provable and Efficient Dataset Distillation for Kernel Ridge Regression
Yilan Chen, Wei Huang, Tsui-Wei Weng
Provable Benefit of Cutout and CutMix for Feature Learning
Junsoo Oh, Chulhee Yun
Provable Benefits of Complex Parameterizations for Structured State Space Models
Yuval Ran-Milo, Eden Lumbroso, Edo Cohen-Karlik et al.
Provable Editing of Deep Neural Networks using Parametric Linear Relaxation
Zhe Tao, Aditya V. Thakur
Provable Partially Observable Reinforcement Learning with Privileged Information
Yang Cai, Xiangyu Liu, Argyris Oikonomou et al.
Provable Posterior Sampling with Denoising Oracles via Tilted Transport
Joan Bruna, Jiequn Han
Provable Tempered Overfitting of Minimal Nets and Typical Nets
Itamar Harel, William M. Hoza, Gal Vardi et al.
Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
Tian Xu, Zhilong Zhang, Ruishuo Chen et al.
Provably Efficient Interactive-Grounded Learning with Personalized Reward
Mengxiao Zhang, Yuheng Zhang, Haipeng Luo et al.
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation
Long-Fei Li, Yu-Jie Zhang, Peng Zhao et al.
Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling
Junyi Li, Heng Huang
Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer
Zhihan Liu, Miao Lu, Shenao Zhang et al.
Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes
Jerry Yao-Chieh Hu, Dennis Wu, Han Liu
Provably Safe Neural Network Controllers via Differential Dynamic Logic
Samuel Teuber, Stefan Mitsch, André Platzer
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning
Dake Bu, Wei Huang, Andi Han et al.
Proving Olympiad Algebraic Inequalities without Human Demonstrations
Chenrui Wei, Mengzhou Sun, Wei Wang
Proving Theorems Recursively
Haiming Wang, Huajian Xin, Zhengying Liu et al.
ProvNeRF: Modeling per Point Provenance in NeRFs as a Stochastic Field
Kiyohiro Nakayama, Mikaela Angelina Uy, Yang You et al.
Proximal Causal Inference With Text Data
Jacob M. Chen, Rohit Bhattacharya, Katherine A. Keith
ProxyFusion: Face Feature Aggregation Through Sparse Experts
Bhavin Jawade, Alexander Stone, Deen Dayal Mohan et al.
Prune and Repaint: Content-Aware Image Retargeting for any Ratio
Feihong Shen, Chao Li, Yifeng Geng et al.
Pruning neural network models for gene regulatory dynamics using data and domain knowledge
Intekhab Hossain, Jonas Fischer, Rebekka Burkholz et al.