Papers
Predicting deliberative outcomes
Vikas Garg, Tommi Jaakkola
Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
Jie Xu, Yunsheng Tian, Pingchuan Ma et al.
Predictive Coding for Locally-Linear Control
Rui Shu, Tung Nguyen, Yinlam Chow et al.
Predictive Multiplicity in Classification
Charles Marx, Flavio Calmon, Berk Ustun
Predictive Sampling with Forecasting Autoregressive Models
Auke Wiggers, Emiel Hoogeboom
Preference Modeling with Context-Dependent Salient Features
Amanda Bower, Laura Balzano
Preselection Bandits
Viktor Bengs, Eyke Hüllermeier
Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification
Hui Ye, Zhiyu Chen, Da-Han Wang et al.
Principled learning method for Wasserstein distributionally robust optimization with local perturbations
Yongchan Kwon, Wonyoung Kim, Joong-Ho Won et al.
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead
Badih Ghazi, Ravi Kumar, Pasin Manurangsi et al.
Privately detecting changes in unknown distributions
Rachel Cummings, Sara Krehbiel, Yuliia Lut et al.
Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni et al.
Private Outsourced Bayesian Optimization
Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low
Private Query Release Assisted by Public Data
Raef Bassily, Albert Cheu, Shay Moran et al.
Private Reinforcement Learning with PAC and Regret Guarantees
Giuseppe Vietri, Borja Balle, Akshay Krishnamurthy et al.
Probing Emergent Semantics in Predictive Agents via Question Answering
Abhishek Das, Federico Carnevale, Hamza Merzic et al.
Problems with Shapley-value-based explanations as feature importance measures
I. Elizabeth Kumar, Suresh Venkatasubramanian, Carlos Scheidegger et al.
Progressive Graph Learning for Open-Set Domain Adaptation
Yadan Luo, Zijian Wang, Zi Huang et al.
Progressive Identification of True Labels for Partial-Label Learning
Jiaqi Lv, Miao Xu, Lei Feng et al.
Projection-free Distributed Online Convex Optimization with $O(\sqrtT)$ Communication Complexity
Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
Projective Preferential Bayesian Optimization
Petrus Mikkola, Milica Todorović, Jari Järvi et al.
Proper Network Interpretability Helps Adversarial Robustness in Classification
Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang et al.
Provable guarantees for decision tree induction: the agnostic setting
Guy Blanc, Jane Lange, Li-Yang Tan
Provable Representation Learning for Imitation Learning via Bi-level Optimization
Sanjeev Arora, Simon Du, Sham Kakade et al.