Papers
On Computing Pairwise Statistics with Local Differential Privacy
Badih Ghazi, Pritish Kamath, Ravi Kumar et al.
On Convergence of Polynomial Approximations to the Gaussian Mixture Entropy
Caleb Dahlke, Jason Pacheco
On Differentially Private Sampling from Gaussian and Product Distributions
Badih Ghazi, Xiao Hu, Ravi Kumar et al.
On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes
Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh et al.
One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization
Minghua Liu, Chao Xu, Haian Jin et al.
One Fits All: Power General Time Series Analysis by Pretrained LM
Tian Zhou, Peisong Niu, xue wang et al.
One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation
Zhiwei Hao, Jianyuan Guo, Kai Han et al.
One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning
Shaochen (Henry) Zhong, Zaichuan You, Jiamu Zhang et al.
One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models
Ba-Hien Tran, Giulio Franzese, Pietro Michiardi et al.
OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling
yifan zhang, Qingsong Wen, xue wang et al.
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning
Zichang Liu, Zhaozhuo Xu, Benjamin Coleman et al.
One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning
Marc Rigter, Bruno Lacerda, Nick Hawes
One-step differentiation of iterative algorithms
Jerome Bolte, Edouard Pauwels, Samuel Vaiter
One-Step Diffusion Distillation via Deep Equilibrium Models
Zhengyang Geng, Ashwini Pokle, J. Zico Kolter
On Evaluating Adversarial Robustness of Large Vision-Language Models
Yunqing Zhao, Tianyu Pang, Chao Du et al.
On Generalization Bounds for Projective Clustering
Maria Sofia Bucarelli, Matilde Larsen, Chris Schwiegelshohn et al.
On Imitation in Mean-field Games
Giorgia Ramponi, Pavel Kolev, Olivier Pietquin et al.
On kernel-based statistical learning theory in the mean field limit
Christian Fiedler, Michael Herty, Sebastian Trimpe
On Learning Latent Models with Multi-Instance Weak Supervision
Kaifu Wang, Efthymia Tsamoura, Dan Roth
On Learning Necessary and Sufficient Causal Graphs
Hengrui Cai, Yixin Wang, Michael I. Jordan et al.
Online Ad Allocation with Predictions
Fabian Spaeh, Alina Ene
Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations
Yiheng Lin, James A. Preiss, Emile Anand et al.
Online Ad Procurement in Non-stationary Autobidding Worlds
Jason Cheuk Nam Liang, Haihao Lu, Baoyu Zhou
Online Clustering of Bandits with Misspecified User Models
Zhiyong Wang, Jize Xie, Xutong Liu et al.
Online Constrained Meta-Learning: Provable Guarantees for Generalization
Siyuan Xu, Minghui Zhu