Papers
Optimizing Black-box Metrics with Adaptive Surrogates
Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan et al.
Optimizing Data Usage via Differentiable Rewards
Xinyi Wang, Hieu Pham, Paul Michel et al.
Optimizing Dynamic Structures with Bayesian Generative Search
Minh Hoang, Carleton Kingsford
Optimizing for the Future in Non-Stationary MDPs
Yash Chandak, Georgios Theocharous, Shiv Shankar et al.
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
Martin Mladenov, Elliot Creager, Omer Ben-Porat et al.
Option Discovery in the Absence of Rewards with Manifold Analysis
Amitay Bar, Ronen Talmon, Ron Meir
OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning
Alexander Vezhnevets, Yuhuai Wu, Maria Eckstein et al.
Oracle Efficient Private Non-Convex Optimization
Seth Neel, Aaron Roth, Giuseppe Vietri et al.
Ordinal Non-negative Matrix Factorization for Recommendation
Olivier Gouvert, Thomas Oberlin, Cédric Févotte
Orthogonalized SGD and Nested Architectures for Anytime Neural Networks
Chengcheng Wan, Henry Hoffmann, Shan Lu et al.
“Other-Play” for Zero-Shot Coordination
Hengyuan Hu, Adam Lerer, Alex Peysakhovich et al.
Overfitting in adversarially robust deep learning
Leslie Rice, Eric Wong, Zico Kolter
PackIt: A Virtual Environment for Geometric Planning
Ankit Goyal, Jia Deng
Parallel Algorithm for Non-Monotone DR-Submodular Maximization
Alina Ene, Huy Nguyen
Parameterized Rate-Distortion Stochastic Encoder
Quan Hoang, Trung Le, Dinh Phung
Parametric Gaussian Process Regressors
Martin Jankowiak, Geoff Pleiss, Jacob Gardner
Partial Trace Regression and Low-Rank Kraus Decomposition
Hachem Kadri, Stephane Ayache, Riikka Huusari et al.
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions
Zhengyang Shen, Lingshen He, Zhouchen Lin et al.
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates
Yang Liu, Hongyi Guo
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh et al.
PENNI: Pruned Kernel Sharing for Efficient CNN Inference
Shiyu Li, Edward Hanson, Hai Li et al.
Perceptual Generative Autoencoders
Zijun Zhang, Ruixiang Zhang, Zongpeng Li et al.
Performative Prediction
Juan Perdomo, Tijana Zrnic, Celestine Mendler-Dünner et al.
Piecewise Linear Regression via a Difference of Convex Functions
Ali Siahkamari, Aditya Gangrade, Brian Kulis et al.