ICML 2024

2,610 papers

Sample-specific Masks for Visual Reprogramming-based Prompting

Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu

On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box

Yi Cai, Gerhard Wunder

LoCoCo: Dropping In Convolutions for Long Context Compression

Ruisi Cai, Yuandong Tian, Zhangyang Wang, Beidi Chen

Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion

Yang Cai, Argyris Oikonomou, Weiqiang Zheng

Flextron: Many-in-One Flexible Large Language Model

Ruisi Cai, Saurav Muralidharan, Greg Heinrich, Hongxu Yin, Zhangyang Wang

Batch and match: black-box variational inference with a score-based divergence

Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles Margossian, Robert M. Gower

Enhancing Cross-Modal Fine-Tuning with Gradually Intermediate Modality Generation

lincan Cai, Shuang Li, Wenxuan Ma, Jingxuan Kang, Binhui Xie

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Tianle Cai, Yuhong Li, Zhengyang Geng, Hongwu Peng, Jason D. Lee

Vocabulary for Universal Approximation: A Linguistic Perspective of Mapping Compositions

Yongqiang Cai

Bridging Environments and Language with Rendering Functions and Vision-Language Models

Théo Cachet, Christopher R Dance, Olivier Sigaud

Learning Associative Memories with Gradient Descent

Vivien Cabannes, Berfin Simsek, Alberto Bietti

Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction

Undral Byambadalai, Tatsushi Oka, Shota Yasui

How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers

Gon Buzaglo, Itamar Harel, Mor Shpigel Nacson, Alon Brutzkus, Nathan Srebro

CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay

Natasha Butt, Blazej Manczak, Auke Wiggers, Corrado Rainone, David W. Zhang

Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, Bowen Baker, Leo Gao

Semantically-correlated memories in a dense associative model

Thomas F Burns

Assessing Large Language Models on Climate Information

Jannis Bulian, Mike S. Schäfer, Afra Amini, Heidi Lam, Massimiliano Ciaramita

Explaining Graph Neural Networks via Structure-aware Interaction Index

Ngoc Bui, Hieu Trung Nguyen, Viet Anh Nguyen, Rex Ying

Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts

Ha Manh Bui, Anqi Liu

Robustness of Nonlinear Representation Learning

Simon Buchholz, Bernhard Schölkopf

Bayesian Optimization of Function Networks with Partial Evaluations

Poompol Buathong, Jiayue Wan, Raul Astudillo, Sam Daulton, Maximilian Balandat

Differentially Private Bias-Term Fine-tuning of Foundation Models

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More

Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn, Kijung Shin

Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples

Dake Bu, Wei Huang, Taiji Suzuki, Ji Cheng, Qingfu Zhang

HAMLET: Graph Transformer Neural Operator for Partial Differential Equations

Andrey Bryutkin, Jiahao Huang, Zhongying Deng, Guang Yang, Carola-Bibiane Schönlieb

Genie: Generative Interactive Environments

Jake Bruce, Michael D Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi

Scalable AI Safety via Doubly-Efficient Debate

Jonah Brown-Cohen, Geoffrey Irving, Georgios Piliouras

Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation

Gavin R Brown, Krishnamurthy Dj Dvijotham, Georgina Evans, Daogao Liu, Adam Smith

Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu’s formula

Kirill Brilliantov, Fedor Pavutnitskiy, Dmitry Pasechnyuk, German Magai

Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees

Marco Bressan, Mauro Sozio

Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics

Manuel Brenner, Florian Hess, Georgia Koppe, Daniel Durstewitz

On dimensionality of feature vectors in MPNNs

César Bravo, Alexander Kozachinskiy, Cristobal Rojas

S$Ω$I: Score-based O-INFORMATION Estimation

Mustapha BOUNOUA, Giulio Franzese, Pietro Michiardi

Improving Neural Additive Models with Bayesian Principles

Kouroche Bouchiat, Alexander Immer, Hugo Yèche, Gunnar Rätsch, Vincent Fortuin

Random matrix theory improved Fréchet mean of symmetric positive definite matrices

Florent Bouchard, Ammar Mian, Malik Tiomoko, Guillaume Ginolhac, Frederic Pascal

A New Computationally Efficient Algorithm to solve Feature Selection for Functional Data Classification in High-dimensional Spaces

Tobia Boschi, Francesca Bonin, Rodrigo Ordonez-Hurtado, Alessandra Pascale, Jonathan P Epperlein

A Dynamical Model of Neural Scaling Laws

Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan

Position: Machine Learning-powered Assessments of the EU Digital Services Act Aid Quantify Policy Impacts on Online Harms

Eleonora Bonel, Luca Nannini, Davide Bassi, Michele Joshua Maggini

Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features

Simone Bombari, Marco Mondelli

How Spurious Features are Memorized: Precise Analysis for Random and NTK Features

Simone Bombari, Marco Mondelli

Shifted Interpolation for Differential Privacy

Jinho Bok, Weijie J Su, Jason Altschuler

Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling

Denis Blessing, Xiaogang Jia, Johannes Esslinger, Francisco Vargas, Gerhard Neumann

Dynamic Survival Analysis with Controlled Latent States

Linus Bleistein, Van Tuan Nguyen, Adeline Fermanian, Agathe Guilloux

Stability Evaluation through Distributional Perturbation Analysis

Jose Blanchet, Peng Cui, JIAJIN LI, Jiashuo Liu

Comparing Graph Transformers via Positional Encodings

Mitchell Black, Zhengchao Wan, Gal Mishne, Amir Nayyeri, Yusu Wang

Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering

Mitchell Black, Lucy Lin, Weng-Keen Wong, Amir Nayyeri

Graph2Tac: Online Representation Learning of Formal Math Concepts

Lasse Blaauwbroek, Mirek Olšák, Jason Rute, Fidel Ivan Schaposnik Massolo, Jelle Piepenbrock

Incorporating Information into Shapley Values: Reweighting via a Maximum Entropy Approach

Darya Biparva, Donatello Materassi

ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections

Massimo Bini, Karsten Roth, Zeynep Akata, Anna Khoreva

Position: Explain to Question not to Justify

Przemyslaw Biecek, Wojciech Samek

Improving fine-grained understanding in image-text pre-training

Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bošnjak

Scalable Safe Policy Improvement for Factored Multi-Agent MDPs

Federico Bianchi, Edoardo Zorzi, Alberto Castellini, Thiago D. Simão, Matthijs T. J. Spaan

How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis

Federico Bianchi, Patrick John Chia, Mert Yuksekgonul, Jacopo Tagliabue, Dan Jurafsky

Naive Bayes Classifiers over Missing Data: Decision and Poisoning

Song Bian, Xiating Ouyang, Zhiwei Fan, Paraschos Koutris

Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning

Yuxuan Bian, Xuan Ju, Jiangtong Li, Zhijian Xu, Dawei Cheng

Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization

Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman

Why do Variational Autoencoders Really Promote Disentanglement?

Pratik Bhowal, Achint Soni, Sirisha Rambhatla

Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling

Raunaq Bhirangi, Chenyu Wang, Venkatesh Pattabiraman, Carmel Majidi, Abhinav Gupta

Total Variation Distance Meets Probabilistic Inference

Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan

Dynamic Facility Location in High Dimensional Euclidean Spaces

Sayan Bhattacharya, Gramoz Goranci, Shaofeng H.-C. Jiang, Yi Qian, Yubo Zhang

Position: Scaling Simulation is Neither Necessary Nor Sufficient for In-the-Wild Robot Manipulation

Homanga Bharadhwaj

Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features

Aleksandr Beznosikov, David Dobre, Gauthier Gidel

Counterfactual Metarules for Local and Global Recourse

Tom Bewley, Salim I. Amoukou, Saumitra Mishra, Daniele Magazzeni, Manuela Veloso

Prompt Sketching for Large Language Models

Luca Beurer-Kellner, Mark Niklas Mueller, Marc Fischer, Martin Vechev

Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation

Luca Beurer-Kellner, Marc Fischer, Martin Vechev

Refining Minimax Regret for Unsupervised Environment Design

Michael Beukman, Samuel Coward, Michael Matthews, Mattie Fellows, Minqi Jiang

Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning

Matteo Bettini, Ryan Kortvelesy, Amanda Prorok

By Tying Embeddings You Are Assuming the Distributional Hypothesis

Francesco Bertolotti, Walter Cazzola

CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations

Jules Berman, Benjamin Peherstorfer

Sequential Disentanglement by Extracting Static Information From A Single Sequence Element

Nimrod Berman, Ilan Naiman, Idan Arbiv, Gal Fadlon, Omri Azencot

Non-clairvoyant Scheduling with Partial Predictions

Ziyad Benomar, Vianney Perchet

Transitional Uncertainty with Layered Intermediate Predictions

Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib

D-Flow: Differentiating through Flows for Controlled Generation

Heli Ben-Hamu, Omri Puny, Itai Gat, Brian Karrer, Uriel Singer

The Role of Learning Algorithms in Collective Action

Omri Ben-Dov, Jake Fawkes, Samira Samadi, Amartya Sanyal

Accelerating Federated Learning with Quick Distributed Mean Estimation

Ran Ben-Basat, Shay Vargaftik, Amit Portnoy, Gil Einziger, Yaniv Ben-Itzhak

Neural Networks Learn Statistics of Increasing Complexity

Nora Belrose, Quintin Pope, Lucia Quirke, Alex Troy Mallen, Xiaoli Fern

Unsupervised Representation Learning of Brain Activity via Bridging Voxel Activity and Functional Connectivity

Ali Behrouz, Parsa Delavari, Farnoosh Hashemi

Standardized Interpretable Fairness Measures for Continuous Risk Scores

Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann

Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations

Jonas Beck, Nathanael Bosch, Michael Deistler, Kyra L. Kadhim, Jakob H. Macke

Graph Neural Networks Use Graphs When They Shouldn’t

Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson

Monotone Individual Fairness

Yahav Bechavod

On Mechanistic Knowledge Localization in Text-to-Image Generative Models

Samyadeep Basu, Keivan Rezaei, Priyatham Kattakinda, Vlad I Morariu, Nanxuan Zhao

A Statistical Framework for Data-dependent Retrieval-Augmented Models

Soumya Basu, Ankit Singh Rawat, Manzil Zaheer

Differentially Private Domain Adaptation with Theoretical Guarantees

Raef Bassily, Corinna Cortes, Anqi Mao, Mehryar Mohri

Local vs. Global Interpretability: A Computational Complexity Perspective

Shahaf Bassan, Guy Amir, Guy Katz

Generalization in Kernel Regression Under Realistic Assumptions

Daniel Barzilai, Ohad Shamir

Neural Diffusion Models

Grigory Bartosh, Dmitry Vetrov, Christian A. Naesseth

Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies

Brian R. Bartoldson, James Diffenderfer, Konstantinos Parasyris, Bhavya Kailkhura

Sliding Down the Stairs: How Correlated Latent Variables Accelerate Learning with Neural Networks

Lorenzo Bardone, Sebastian Goldt

To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models

George-Octavian Barbulescu, Peter Triantafillou

Scale-Free Image Keypoints Using Differentiable Persistent Homology

Giovanni Barbarani, Francesco Vaccarino, Gabriele Trivigno, Marco Guerra, Gabriele Berton

Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products

Guy Bar-Shalom, Beatrice Bevilacqua, Haggai Maron

Stochastic positional embeddings improve masked image modeling

Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent

Graph Out-of-Distribution Detection Goes Neighborhood Shaping

Tianyi Bao, Qitian Wu, Zetian Jiang, Yiting Chen, Jiawei Sun

Self-attention Networks Localize When QK-eigenspectrum Concentrates

Han Bao, Ryuichiro Hataya, Ryo Karakida

Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective

Yajie Bao, Michael Crawshaw, Mingrui Liu

VNN: Verification-Friendly Neural Networks with Hard Robustness Guarantees

Anahita Baninajjar, Ahmed Rezine, Amir Aminifar

Dynamic Metric Embedding into lp Space

Kiarash Banihashem, MohammadTaghi Hajiaghayi, Dariusz Rafal Kowalski, Jan Olkowski, Max Springer

A Dynamic Algorithm for Weighted Submodular Cover Problem

Kiarash Banihashem, Samira Goudarzi, MohammadTaghi Hajiaghayi, Peyman Jabbarzade, Morteza Monemizadeh

Relational DNN Verification With Cross Executional Bound Refinement

Debangshu Banerjee, Gagandeep Singh