Papers
On Tradeoffs in Learning-Augmented Algorithms
Ziyad Benomar, Vianney Perchet
Optimal downsampling for Imbalanced Classification with Generalized Linear Models
Yan Chen, Jose Blanchet, Krzysztof Dembczynski et al.
Optimal estimation of linear non-Gaussian structure equation models
Sunmin Oh, Seungsu Han, Gunwoong Park
Optimal Multi-Objective Best Arm Identification with Fixed Confidence
Zhirui Chen, P. N. Karthik, Yeow Meng Chee et al.
Optimal Stochastic Trace Estimation in Generative Modeling
Xinyang Liu, Hengrong Du, Wei Deng et al.
Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs
Krzysztof Marcin Choromanski, Isaac Reid, Arijit Sehanobish et al.
Optimising Clinical Federated Learning through Mode Connectivity-based Model Aggregation
Anshul Thakur, Soheila Molaei, Patrick Schwab et al.
Optimistic Safety for Online Convex Optimization with Unknown Linear Constraints
Spencer Hutchinson, Tianyi Chen, Mahnoosh Alizadeh
Optimizing Neural Network Training and Quantization with Rooted Logistic Objectives
Zhu Wang, Praveen Raj Veluswami, Harsh Mishra et al.
Ordered $\mathcalV$-information Growth: A Fresh Perspective on Shared Information
Rohan Ghosh, Mehul Motani
Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness
Nikola Pavlovic, Sudeep Salgia, Qing Zhao
Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs
Swetha Ganesh, Washim Uddin Mondal, Vaneet Aggarwal
Out-of-distribution robustness for multivariate analysis via causal regularisation
Homer Durand, Gherardo Varando, Nathan Mankovich et al.
Parabolic Continual Learning
Haoming Yang, Ali Hasan, Vahid Tarokh
Parallel Backpropagation for Inverse of a Convolution with Application to Normalizing Flows
Sandeep Nagar, Girish Varma
Parameter estimation in state space models using particle importance sampling
Yuxiong Gao, Wentao Li, Rong Chen
Pareto Set Identification With Posterior Sampling
Cyrille Kone, Marc Jourdan, Emilie Kaufmann
Partial Information Decomposition for Data Interpretability and Feature Selection
Charles Westphal, Stephen Hailes, Mirco Musolesi
Paths and Ambient Spaces in Neural Loss Landscapes
Daniel Dold, Julius Kobialka, Nicolai Palm et al.
Perfect Recovery for Random Geometric Graph Matching with Shallow Graph Neural Networks
Suqi Liu, Morgane Austern
Performative Prediction on Games and Mechanism Design
António Góis, Mehrnaz Mofakhami, Fernando P. Santos et al.
Performative Reinforcement Learning with Linear Markov Decision Process
Debmalya Mandal, Goran Radanovic
Permutation Invariant Functions: Statistical Testing, Density Estimation, and Metric Entropy
Wee Chaimanowong, Ying Zhu
Personalized Convolutional Dictionary Learning of Physiological Time Series
Axel Roques, Samuel Gruffaz, Kyurae Kim et al.
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning
Boning Zhang, Dongzhu Liu, Osvaldo Simeone et al.