ICML 2023

1,828 papers

Differentially Private Distributed Bayesian Linear Regression with MCMC

Baris Alparslan, Sinan Yıldırım, Ilker Birbil

On the Privacy-Robustness-Utility Trilemma in Distributed Learning

Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan

A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models

James Urquhart Allingham, Jie Ren, Michael W Dusenberry, Xiuye Gu, Yin Cui

Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think

Christian H.X. Ali Mehmeti-Göpel, Jan Disselhoff

The Saddle-Point Method in Differential Privacy

Wael Alghamdi, Juan Felipe Gomez, Shahab Asoodeh, Flavio Calmon, Oliver Kosut

Recasting Self-Attention with Holographic Reduced Representations

Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt

Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data

Ahmet Alacaoglu, Hanbaek Lyu

Towards credible visual model interpretation with path attribution

Naveed Akhtar, Mohammad A. A. K. Jalwana

Atari-5: Distilling the Arcade Learning Environment down to Five Games

Matthew Aitchison, Penny Sweetser, Marcus Hutter

Sequential Underspecified Instrument Selection for Cause-Effect Estimation

Elisabeth Ailer, Jason Hartford, Niki Kilbertus

Interventional Causal Representation Learning

Kartik Ahuja, Divyat Mahajan, Yixin Wang, Yoshua Bengio

Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies

Gati V Aher, Rosa I. Arriaga, Adam Tauman Kalai

Explaining the effects of non-convergent MCMC in the training of Energy-Based Models

Elisabeth Agoritsas, Giovanni Catania, Aurélien Decelle, Beatriz Seoane

Constrained Causal Bayesian Optimization

Virginia Aglietti, Alan Malek, Ira Ktena, Silvia Chiappa

Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability

Anass Aghbalou, Guillaume Staerman

Scaling Laws for Generative Mixed-Modal Language Models

Armen Aghajanyan, LILI YU, Alexis CONNEAU, Wei-Ning Hsu, Karen Hambardzumyan

Adaptive IMLE for Few-shot Pretraining-free Generative Modelling

Mehran Aghabozorgi, Shichong Peng, Ke Li

SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification

Pranjal Aggarwal, Ameet Deshpande, Karthik R Narasimhan

Global optimality of Elman-type RNNs in the mean-field regime

Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee

Second-order regression models exhibit progressive sharpening to the edge of stability

Atish Agarwala, Fabian Pedregosa, Jeffrey Pennington

SAM operates far from home: eigenvalue regularization as a dynamical phenomenon

Atish Agarwala, Yann Dauphin

BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming

Steven Adams, Andrea Patane, Morteza Lahijanian, Luca Laurenti

Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects

Naoufal Acharki, Ramiro Lugo, Antoine Bertoncello, Josselin Garnier

Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making

Axel Abels, Tom Lenaerts, Vito Trianni, Ann Nowe

Toward Large Kernel Models

Amirhesam Abedsoltan, Mikhail Belkin, Parthe Pandit

Generalization on the Unseen, Logic Reasoning and Degree Curriculum

Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Kevin Rizk

ClusterFuG: Clustering Fully connected Graphs by Multicut

Ahmed Abbas, Paul Swoboda

Data Structures for Density Estimation

Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan