← Authors

Gaël RICHARD

14 papers · 2016–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) 🏃 Academic Marathon (9) 🌈 Renaissance Researcher (6) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (31) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (15) 🏆 Keyword Champion 🔥 Unstoppable (5) 🗃️ Keyword Collector (67) 💎 Century Club (14)

Conferences

NIPS (6) ICML (5) COLT (1) EMNLP (1) INTERSPEECH (1)

Top co-authors

Umut Simsekli (8) Slim Essid (4) Mathieu Fontaine (3) Victor Letzelter (3) Than Huy Nguyen (2) Mickaël Chen (2) David Perera (2) Patrick Pérez (2) Taylan Cemgil (2) Roland Badeau (2)

Keywords

stochastic gradient (3) markov chain monte carlo (3) non-convex optimization (2) bayesian inference (2) stochastic gradient markov chain monte carlo (2) multiple choice learning (2) generalization bound (2) heavy-tailed distribution (2) stochastic gradient descent (2) quasi-newton method (2) acoustic modeling (1) nonnegative matrix factorization (1) neural network optimization (1) zero-shot learning (1) langevin dynamics (1) deep learning (1) audio classification (1) posterior sampling (1) speech dereverberation (1) simulated annealing (1)

Papers

iKnow-audio: Integrating Knowledge Graphs with Audio-Language Models EMNLP 2025
Speech dereverberation constrained on room impulse response characteristics INTERSPEECH 2024
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing NIPS 2024
Winner-takes-all learners are geometry-aware conditional density estimators ICML 2024
Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis NIPS 2023
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms COLT 2022
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF NIPS 2022
Relative Positional Encoding for Transformers with Linear Complexity ICML 2021
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks NIPS 2021
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization ICML 2019
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise NIPS 2019
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization ICML 2018
Stochastic Quasi-Newton Langevin Monte Carlo ICML 2016
Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo NIPS 2016