Papers
POEM: Out-of-Distribution Detection with Posterior Sampling
Yifei Ming, Ying Fan, Yixuan Li
POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging
Shishir G. Patil, Paras Jain, Prabal Dutta et al.
PoF: Post-Training of Feature Extractor for Improving Generalization
Ikuro Sato, Yamada Ryota, Masayuki Tanaka et al.
Policy Diagnosis via Measuring Role Diversity in Cooperative Multi-agent RL
Siyi Hu, Chuanlong Xie, Xiaodan Liang et al.
Policy Gradient Method For Robust Reinforcement Learning
Yue Wang, Shaofeng Zou
Popular decision tree algorithms are provably noise tolerant
Guy Blanc, Jane Lange, Ali Malik et al.
Position Prediction as an Effective Pretraining Strategy
Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram et al.
Power-Law Escape Rate of SGD
Takashi Mori, Liu Ziyin, Kangqiao Liu et al.
Practical Almost-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering
Lorenzo Orecchia, Konstantinos Ameranis, Charalampos Tsourakakis et al.
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization
Jonathan Wenger, Geoff Pleiss, Philipp Hennig et al.
Predicting Out-of-Distribution Error with the Projection Norm
Yaodong Yu, Zitong Yang, Alexander Wei et al.
Principal Component Flows
Edmond Cunningham, Adam D Cobb, Susmit Jha
Principled Knowledge Extrapolation with GANs
Ruili Feng, Jie Xiao, Kecheng Zheng et al.
Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt
Sören Mindermann, Jan M Brauner, Muhammed T Razzak et al.
Privacy for Free: How does Dataset Condensation Help Privacy?
Tian Dong, Bo Zhao, Lingjuan Lyu
Private Adaptive Optimization with Side information
Tian Li, Manzil Zaheer, Sashank Reddi et al.
Private frequency estimation via projective geometry
Vitaly Feldman, Jelani Nelson, Huy Nguyen et al.
Private optimization in the interpolation regime: faster rates and hardness results
Hilal Asi, Karan Chadha, Gary Cheng et al.
Private Streaming SCO in $\ell_p$ geometry with Applications in High Dimensional Online Decision Making
Yuxuan Han, Zhicong Liang, Zhipeng Liang et al.
Probabilistically Robust Learning: Balancing Average and Worst-case Performance
Alexander Robey, Luiz Chamon, George J. Pappas et al.
Probabilistic Bilevel Coreset Selection
Xiao Zhou, Renjie Pi, Weizhong Zhang et al.
Probabilistic ODE Solutions in Millions of Dimensions
Nicholas Krämer, Nathanael Bosch, Jonathan Schmidt et al.
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning
Jun Xia, Lirong Wu, Ge Wang et al.
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
Hui-Po Wang, Sebastian Stich, Yang He et al.
Prompting Decision Transformer for Few-Shot Policy Generalization
Mengdi Xu, Yikang Shen, Shun Zhang et al.