Papers
Probabilistic Time Series Forecasting with Shape and Temporal Diversity
Vincent LE GUEN, Nicolas THOME
Probably Approximately Correct Constrained Learning
Luiz Chamon, Alejandro Ribeiro
Program Synthesis with Pragmatic Communication
Yewen Pu, Kevin Ellis, Marta Kryven et al.
Projected Stein Variational Gradient Descent
Peng Chen, Omar Ghattas
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method
Kiran K Thekumparampil, Prateek Jain, Praneeth Netrapalli et al.
Projection Robust Wasserstein Distance and Riemannian Optimization
Tianyi Lin, Chenyou Fan, Nhat Ho et al.
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
Julien Roy, Paul Barde, Félix Harvey et al.
Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method
Qi Zhou, Yufei Kuang, Zherui Qiu et al.
Prophet Attention: Predicting Attention with Future Attention
Fenglin Liu, Xuancheng Ren, Xian Wu et al.
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning
Sirisha Rambhatla, Xingguo Li, Jarvis Haupt
Provable Overlapping Community Detection in Weighted Graphs
Jimit Majmudar, Stephen Vavasis
Provably adaptive reinforcement learning in metric spaces
Tongyi Cao, Akshay Krishnamurthy
Provably Consistent Partial-Label Learning
Lei Feng, Jiaqi Lv, Bo Han et al.
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning
Fei Feng, Ruosong Wang, Wotao Yin et al.
Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach
Luofeng Liao, You-Lin Chen, Zhuoran Yang et al.
Provably Efficient Neural GTD for Off-Policy Learning
Hoi-To Wai, Zhuoran Yang, Zhaoran Wang et al.
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits
Jack Parker-Holder, Vu Nguyen, Stephen J. Roberts
Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations
Zhuoran Yang, Chi Jin, Zhaoran Wang et al.
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration
Andrea Zanette, Alessandro Lazaric, Mykel J Kochenderfer et al.
Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration
Yao Liu, Adith Swaminathan, Alekh Agarwal et al.
Provably Robust Metric Learning
Lu Wang, Xuanqing Liu, Jinfeng Yi et al.
Proximal Mapping for Deep Regularization
Mao Li, Yingyi Ma, Xinhua Zhang
Proximity Operator of the Matrix Perspective Function and its Applications
Joong-Ho (Johann) Won
Pruning Filter in Filter
Fanxu Meng, Hao Cheng, Ke Li et al.