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2020 – today
- 2023
[c10]Tolga Ergen, Halil Ibrahim Gulluk, Jonathan Lacotte, Mert Pilanci:
Globally Optimal Training of Neural Networks with Threshold Activation Functions. ICLR 2023- [i14]Tolga Ergen, Halil Ibrahim Gulluk, Jonathan Lacotte, Mert Pilanci:
Globally Optimal Training of Neural Networks with Threshold Activation Functions. CoRR abs/2303.03382 (2023) - 2022
- [j2]Jonathan Lacotte
, Mert Pilanci:
Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds. IEEE Trans. Inf. Theory 68(5): 3281-3303 (2022) - [c9]Yifei Wang, Jonathan Lacotte, Mert Pilanci:
The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: an Exact Characterization of Optimal Solutions. ICLR 2022 - 2021
- [c8]Jonathan Lacotte, Yifei Wang, Mert Pilanci:
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality. ICML 2021: 5926-5936 - [c7]Michal Derezinski, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney:
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update. NeurIPS 2021: 2835-2847 - [i13]Jonathan Lacotte, Mert Pilanci:
Fast Convex Quadratic Optimization Solvers with Adaptive Sketching-based Preconditioners. CoRR abs/2104.14101 (2021) - [i12]Jonathan Lacotte, Yifei Wang, Mert Pilanci:
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality. CoRR abs/2105.07291 (2021) - [i11]Michal Derezinski, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney:
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update. CoRR abs/2107.07480 (2021) - 2020
- [c6]Jonathan Lacotte, Mert Pilanci:
Optimal Randomized First-Order Methods for Least-Squares Problems. ICML 2020: 5587-5597 - [c5]Jonathan Lacotte, Sifan Liu, Edgar Dobriban, Mert Pilanci:
Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform. NeurIPS 2020 - [c4]Jonathan Lacotte, Mert Pilanci:
Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization. NeurIPS 2020 - [i10]Jonathan Lacotte, Sifan Liu, Edgar Dobriban, Mert Pilanci:
Limiting Spectrum of Randomized Hadamard Transform and Optimal Iterative Sketching Methods. CoRR abs/2002.00864 (2020) - [i9]Jonathan Lacotte, Mert Pilanci:
Optimal Randomized First-Order Methods for Least-Squares Problems. CoRR abs/2002.09488 (2020) - [i8]Jonathan Lacotte, Mert Pilanci:
Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization. CoRR abs/2006.05874 (2020) - [i7]Jonathan Lacotte, Mert Pilanci:
All Local Minima are Global for Two-Layer ReLU Neural Networks: The Hidden Convex Optimization Landscape. CoRR abs/2006.05900 (2020) - [i6]Jonathan Lacotte, Mert Pilanci:
Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds. CoRR abs/2012.07054 (2020)
2010 – 2019
- 2019
- [c3]Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow, Marco Pavone:
Risk-Sensitive Generative Adversarial Imitation Learning. AISTATS 2019: 2154-2163 - [c2]Margaret P. Chapman, Jonathan Lacotte, Aviv Tamar, Donggun Lee, Kevin M. Smith, Victoria Cheng, Jaime F. Fisac, Susmit Jha, Marco Pavone, Claire J. Tomlin:
A Risk-Sensitive Finite-Time Reachability Approach for Safety of Stochastic Dynamic Systems. ACC 2019: 2958-2963 - [c1]Jonathan Lacotte, Mert Pilanci, Marco Pavone:
High-Dimensional Optimization in Adaptive Random Subspaces. NeurIPS 2019: 10846-10856 - [i5]Margaret P. Chapman, Jonathan Lacotte, Aviv Tamar, Donggun Lee, Kevin M. Smith, Victoria Cheng, Jaime F. Fisac, Susmit Jha, Marco Pavone, Claire J. Tomlin:
A Risk-Sensitive Finite-Time Reachability Approach for Safety of Stochastic Dynamic Systems. CoRR abs/1902.11277 (2019) - [i4]Jonathan Lacotte, Mert Pilanci, Marco Pavone:
High-Dimensional Optimization in Adaptive Random Subspaces. CoRR abs/1906.11809 (2019) - [i3]Jonathan Lacotte, Mert Pilanci:
Faster Least Squares Optimization. CoRR abs/1911.02675 (2019) - 2018
- [j1]Sumeet Singh, Jonathan Lacotte, Anirudha Majumdar, Marco Pavone:
Risk-sensitive inverse reinforcement learning via semi- and non-parametric methods. Int. J. Robotics Res. 37(13-14) (2018) - [i2]Jonathan Lacotte, Yinlam Chow, Mohammad Ghavamzadeh, Marco Pavone:
Risk-Sensitive Generative Adversarial Imitation Learning. CoRR abs/1808.04468 (2018) - 2017
- [i1]Sumeet Singh, Jonathan Lacotte, Anirudha Majumdar, Marco Pavone:
Risk-sensitive Inverse Reinforcement Learning via Semi- and Non-Parametric Methods. CoRR abs/1711.10055 (2017)
Coauthor Index
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