International Conference on Machine Learning
ICML
A*
CORE rank
CORE rank (raw)
A*
Acceptance rate
27.5% (2024)
Fields of research
Machine Learning
Papers indexed
17,065
1988–2025
Papers per year
19883,341 peak2025
Most published authors
ICML papers
17,065 records sourced from DBLP. Search titles, filter by year, sort by recency.
| Year | Title | Authors |
|---|---|---|
| 2025 | Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching. | Nabeel Seedat, Mihaela van der Schaar |
| 2025 | Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation. | D. Sculley, William Cukierski, Phil Culliton, Sohier Dane, Maggie Demkin, Ryan Holbrook, Addison Howard, Paul Mooney, Walter Reade, Meg Risdal, Nate Keating |
| 2025 | Differentially Private Federated k-Means Clustering with Server-Side Data. | Jonathan Scott, Christoph H. Lampert, David Saulpic |
| 2025 | Cover learning for large-scale topology representation. | Luis Scoccola, Uzu Lim, Heather A. Harrington |
| 2025 | Learning Representations of Instruments for Partial Identification of Treatment Effects. | Jonas Schweisthal, Dennis Frauen, Maresa Schrder, Konstantin Hess, Niki Kilbertus, Stefan Feuerriegel |
| 2025 | The Disparate Benefits of Deep Ensembles. | Kajetan Schweighofer, Adrin Arnaiz-Rodrguez, Sepp Hochreiter, Nuria Oliver |
| 2025 | Mastering Board Games by External and Internal Planning with Language Models. | John Schultz, Jakub Admek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev |
| 2025 | Adjustment for Confounding using Pre-Trained Representations. | Rickmer Schulte, David Rgamer, Thomas Nagler |
| 2025 | Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting. | Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac, Anderson Schneider, Yuriy Nevmyvaka, Stephan Gnnemann |
| 2025 | Temperature-Annealed Boltzmann Generators. | Henrik Schopmans, Pascal Friederich |
| 2025 | Implicit Language Models are RNNs: Balancing Parallelization and Expressivity. | Mark Schne, Babak Rahmani, Heiner Kremer, Fabian Falck, Hitesh Ballani, Jannes Gladrow |
| 2025 | Hyperband-based Bayesian Optimization for Black-box Prompt Selection. | Lennart Schneider, Martin Wistuba, Aaron Klein, Jacek Golebiowski, Giovanni Zappella, Felice Antonio Merra |
| 2025 | Generative Intervention Models for Causal Perturbation Modeling. | Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schlkopf, Andreas Krause |
| 2025 | A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks. | Thomas Schmied, Thomas Adler, Vihang Prakash Patil, Maximilian Beck, Korbinian Pppel, Johannes Brandstetter, Gnter Klambauer, Razvan Pascanu, Sepp Hochreiter |
| 2025 | FastCAV: Efficient Computation of Concept Activation Vectors for Explaining Deep Neural Networks. | Laines Schmalwasser, Niklas Penzel, Joachim Denzler, Julia Niebling |
| 2025 | Learning the RoPEs: Better 2D and 3D Position Encodings with STRING. | Connor Schenck, Isaac Reid, Mithun George Jacob, Alex Bewley, Joshua Ainslie, David Rendleman, Deepali Jain, Mohit Sharma, Kumar Avinava Dubey, Ayzaan Wahid, Sumeet Singh, Ren Wagner, Tianli Ding, Chuyuan Fu, Arunkumar Byravan, Jake Varley, Alexey A. Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, Krzysztof Marcin Choromanski |
| 2025 | The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training. | Fabian Schaipp, Alexander Hgele, Adrien B. Taylor, Umut Simsekli, Francis Bach |
| 2025 | Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive? | Rylan Schaeffer, Hailey Schoelkopf, Brando Miranda, Gabriel Mukobi, Varun Madan, Adam Ibrahim, Herbie Bradley, Stella Biderman, Sanmi Koyejo |
| 2025 | How Do Large Language Monkeys Get Their Power (Laws)? | Rylan Schaeffer, Joshua Kazdan, John Hughes, Jordan Juravsky, Sara Price, Aengus Lynch, Erik Jones, Robert Kirk, Azalia Mirhoseini, Sanmi Koyejo |
| 2025 | Symmetry-Robust 3D Orientation Estimation. | Christopher Scarvelis, David Ben-Haim, Paul Zhang |
| 2025 | ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals. | Utkarsh Saxena, Sayeh Sharify, Kaushik Roy, Xin Wang |
| 2025 | Making Hard Problems Easier with Custom Data Distributions and Loss Regularization: A Case Study in Modular Arithmetic. | Eshika Saxena, Alberto Alfarano, Emily Wenger, Kristin E. Lauter |
| 2025 | Natural Perturbations for Black-box Training of Neural Networks by Zeroth-Order Optimization. | Hiroshi Sawada, Kazuo Aoyama, Yuya Hikima |
| 2025 | NestQuant: nested lattice quantization for matrix products and LLMs. | Semyon Savkin, Eitan Porat, Or Ordentlich, Yury Polyanskiy |
| 2025 | WeGeFT: Weight‑Generative Fine-Tuning for Multi-Faceted Efficient Adaptation of Large Models. | Chinmay Savadikar, Xi Song, Tianfu Wu |
1,001–1,025 of 17,065← PreviousNext →
Comparable venues
Other A*/A conferences filed under the same field of research.
- A*ICLRInternational Conference on Learning Representations
- AAISTATSInternational Conference on Artificial Intelligence and Statistics
- A*COLTConference on Learning Theory
- APPSNParallel Problem Solving from Nature
- AECML PKDDEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008)
- A*NeurIPSAdvances in Neural Information Processing Systems (was NIPS)