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Leonard Adolphs
Leonard Adolphs
ETH Zürich
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Local Saddle Point Optimization: A Curvature Exploitation Approach
L Adolphs, H Daneshmand, A Lucchi, T Hofmann
AISTATS 2019: International Conference on Artificial Intelligence and Statistics, 2018
932018
LeDeepChef: Deep Reinforcement Learning Agent for Families of Text-Based Games
L Adolphs, T Hofmann
AAAI 2020: Conference on Artificial Intelligence, 2019
302019
Ellipsoidal Trust Region Methods for Neural Network Training
L Adolphs, J Kohler, A Lucchi
NeurIPS 2019 Workshop: Beyond First-Order Optimization Methods in Machine …, 2019
9*2019
Reason first, then respond: Modular Generation for Knowledge-infused Dialogue
L Adolphs, K Shuster, J Urbanek, A Szlam, J Weston
arXiv preprint arXiv:2111.05204, 2021
42021
Boosting search engines with interactive agents
L Adolphs, B Boerschinger, C Buck, MC Huebscher, M Ciaramita, ...
arXiv preprint arXiv:2109.00527, 2021
42021
Language models that seek for knowledge: Modular search & generation for dialogue and prompt completion
K Shuster, M Komeili, L Adolphs, S Roller, A Szlam, J Weston
arXiv preprint arXiv:2203.13224, 2022
32022
Non convex-concave saddle point optimization
L Adolphs
ETH Zurich, 2018
32018
How to Query Language Models?
L Adolphs, S Dhuliawala, T Hofmann
arXiv preprint arXiv:2108.01928, 2021
22021
Calibration of Machine Reading Systems at Scale
S Dhuliawala, L Adolphs, R Das, M Sachan
arXiv preprint arXiv:2203.10623, 2022
2022
Adaptive norms for deep learning with regularized Newton methods
J Kohler, L Adolphs, A Lucchi
arXiv preprint arXiv:1905.09201, 2019
2019
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Artículos 1–10