Papers
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation
Wei-Ning Chen, Dan Song, Ayfer Ozgur et al.
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?
Xiaoxiao Sun, Nidham Gazagnadou, Vivek Sharma et al.
Privacy Auditing with One (1) Training Run
Thomas Steinke, Milad Nasr, Matthew Jagielski
Private Distribution Learning with Public Data: The View from Sample Compression
Shai Ben-David, Alex Bie, Clément L Canonne et al.
Private estimation algorithms for stochastic block models and mixture models
Hongjie Chen, Vincent Cohen-Addad, Tommaso d’Orsi et al.
Private Everlasting Prediction
Moni Naor, Kobbi Nissim, Uri Stemmer et al.
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance
Jingfeng Wu, Wennan Zhu, Peter Kairouz et al.
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks
Daogao Liu, Arun Ganesh, Sewoong Oh et al.
Probabilistic Exponential Integrators
Nathanael Bosch, Philipp Hennig, Filip Tronarp
Probabilistic Inference in Reinforcement Learning Done Right
Jean Tarbouriech, Tor Lattimore, Brendan O'Donoghue
Probabilistic Invariant Learning with Randomized Linear Classifiers
Leonardo Cotta, Gal Yehuda, Assaf Schuster et al.
Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs
Dominik Straub, Matthias Schultheis, Heinz Koeppl et al.
Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantisation.
Chris Subia-Waud, Srinandan Dasmahapatra
PrObeD: Proactive Object Detection Wrapper
Vishal Asnani, Abhinav Kumar, Suya You et al.
ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab
Jieming Cui, Ziren Gong, Baoxiong Jia et al.
PRODIGY: Enabling In-context Learning Over Graphs
Qian Huang, Hongyu Ren, Peng Chen et al.
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference
Don Dennis, Abhishek Shetty, Anish Prasad Sevekari et al.
Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems
Morteza Boroun, Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh
Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem
Jincheng Cao, Ruichen Jiang, Nazanin Abolfazli et al.
Projection-Free Online Convex Optimization via Efficient Newton Iterations
Khashayar Gatmiry, Zak Mhammedi
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models
Sungik Choi, Hankook Lee, Honglak Lee et al.
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation
Zhengyi Wang, Cheng Lu, Yikai Wang et al.
Promises and Pitfalls of Threshold-based Auto-labeling
Harit Vishwakarma, Heguang Lin, Frederic Sala et al.
Prompt-augmented Temporal Point Process for Streaming Event Sequence
Siqiao Xue, Yan Wang, Zhixuan Chu et al.
PromptIR: Prompting for All-in-One Image Restoration
Vaishnav Potlapalli, Syed Waqas Zamir, Salman H Khan et al.