Papers
Overcoming Multi-model Forgetting
Yassine Benyahia, Kaicheng Yu, Kamil Bennani Smires et al.
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?
Samet Oymak, Mahdi Soltanolkotabi
PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits
Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
PAC Learnability of Node Functions in Networked Dynamical Systems
Abhijin Adiga, Chris J Kuhlman, Madhav Marathe et al.
PA-GD: On the Convergence of Perturbed Alternating Gradient Descent to Second-Order Stationary Points for Structured Nonconvex Optimization
Songtao Lu, Mingyi Hong, Zhengdao Wang
Parameter-Efficient Transfer Learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski et al.
Pareto Optimal Streaming Unsupervised Classification
Soumya Basu, Steven Gutstein, Brent Lance et al.
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization
Seungyong Moon, Gaon An, Hyun Oh Song
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
Samuel Wiqvist, Pierre-Alexandre Mattei, Umberto Picchini et al.
Partially Linear Additive Gaussian Graphical Models
Sinong Geng, Minhao Yan, Mladen Kolar et al.
Particle Flow Bayes’ Rule
Xinshi Chen, Hanjun Dai, Le Song
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models
Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani et al.
Per-Decision Option Discounting
Anna Harutyunyan, Peter Vrancx, Philippe Hamel et al.
Phaseless PCA: Low-Rank Matrix Recovery from Column-wise Phaseless Measurements
Seyedehsara Nayer, Praneeth Narayanamurthy, Namrata Vaswani
Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size!
Niels Ipsen, Lars Kai Hansen
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers
Ernest Ryu, Jialin Liu, Sicheng Wang et al.
Poission Subsampled Rényi Differential Privacy
Yuqing Zhu, Yu-Xiang Wang
Policy Certificates: Towards Accountable Reinforcement Learning
Christoph Dann, Lihong Li, Wei Wei et al.
Policy Consolidation for Continual Reinforcement Learning
Christos Kaplanis, Murray Shanahan, Claudia Clopath
POLITEX: Regret Bounds for Policy Iteration using Expert Prediction
Yasin Abbasi-Yadkori, Peter Bartlett, Kush Bhatia et al.
POPQORN: Quantifying Robustness of Recurrent Neural Networks
Ching-Yun Ko, Zhaoyang Lyu, Lily Weng et al.
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
Daniel Ho, Eric Liang, Xi Chen et al.
Position-aware Graph Neural Networks
Jiaxuan You, Rex Ying, Jure Leskovec
Power k-Means Clustering
Jason Xu, Kenneth Lange