Ineq-Comp: Benchmarking Human-Intuitive Compositional Reasoning in Automated Theorem Proving on Inequalities.
CoRR, May, 2025
Task Generalization With AutoRegressive Compositional Structure: Can Learning From <i>D</i> Tasks Generalize to <i>D</i><sup>T</sup> Tasks?
CoRR, February, 2025
Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving.
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CoRR, February, 2025
UNDIAL: Self-Distillation with Adjusted Logits for Robust Unlearning in Large Language Models.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025
From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Unmemorization in Large Language Models via Self-Distillation and Deliberate Imagination.
CoRR, 2024
Deep hybrid model with satellite imagery: how to combine demand modeling and computer vision for behavior analysis?
CoRR, 2023
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity.
Proceedings of the International Conference on Machine Learning, 2022
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Stochastic Optimization with Non-stationary Noise.
CoRR, 2020
On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions.
CoRR, 2020
On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions.
CoRR, 2020
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions.
Proceedings of the 37th International Conference on Machine Learning, 2020
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration.
SIAM J. Optim., 2019
ResNet with one-neuron hidden layers is a Universal Approximator.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Catalyst for Gradient-based Nonconvex Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Generic acceleration schemes for gradient-based optimization in machine learning. (Algorithmes d'accélération générique pour les méthodes d'optimisation en apprentissage statistique).
PhD thesis, 2017
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice.
J. Mach. Learn. Res., 2017
A Universal Catalyst for First-Order Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015