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ORCIDReza Babanezhad 0001
2020 – today
- 2024
[j2]Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar:
Promoting Exploration in Memory-Augmented Adam using Critical Momenta. Trans. Mach. Learn. Res. 2024 (2024)- [c16]Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh, Xingzhi Guo, Deqing Yang, Yanghua Xiao:
Iterative Methods via Locally Evolving Set Process. NeurIPS 2024 - [i21]Anh Dang, Reza Babanezhad, Sharan Vaswani:
Noise-adaptive (Accelerated) Stochastic Heavy-Ball Momentum. CoRR abs/2401.06738 (2024) - [i20]Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh, Xingzhi Guo, Deqing Yang, Yanghua Xiao:
Iterative Methods via Locally Evolving Set Process. CoRR abs/2410.15020 (2024) - [i19]Reza Asad, Reza Babanezhad, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani:
Fast Convergence of Softmax Policy Mirror Ascent. CoRR abs/2411.12042 (2024) - [i18]Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Gintare Karolina Dziugaite, Razvan Pascanu, Sarath Chandar:
Torque-Aware Momentum. CoRR abs/2412.18790 (2024) - 2023
- [c15]Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux:
Target-based Surrogates for Stochastic Optimization. ICML 2023: 18614-18651 - [c14]Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh:
Fast Online Node Labeling for Very Large Graphs. ICML 2023: 42658-42697 - [c13]Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad Harikandeh, Nicolas Le Roux:
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees. NeurIPS 2023 - [i17]Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Nicolas Le Roux:
Target-based Surrogates for Stochastic Optimization. CoRR abs/2302.02607 (2023) - [i16]Sharan Vaswani, Amirreza Kazemi, Reza Babanezhad, Nicolas Le Roux:
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees. CoRR abs/2305.15249 (2023) - [i15]Baojian Zhou, Yifan Sun, Reza Babanezhad:
Fast Online Node Labeling for Very Large Graphs. CoRR abs/2305.16257 (2023) - [i14]Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar:
Promoting Exploration in Memory-Augmented Adam using Critical Momenta. CoRR abs/2307.09638 (2023) - 2022
- [j1]Benjamin Dubois-Taine
, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien:
SVRG meets AdaGrad: painless variance reduction. Mach. Learn. 111(12): 4359-4409 (2022) - [c12]Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad:
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent. ICML 2022: 22015-22059 - [c11]Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesváari, Doina Precup:
Towards painless policy optimization for constrained MDPs. UAI 2022: 895-905 - [i13]Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesvári, Doina Precup:
Towards Painless Policy Optimization for Constrained MDPs. CoRR abs/2204.05176 (2022) - 2021
- [c10]Rémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien:
An Analysis of the Adaptation Speed of Causal Models. AISTATS 2021: 775-783 - [c9]Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang:
Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport. ICML 2021: 7033-7044 - [i12]Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien:
SVRG Meets AdaGrad: Painless Variance Reduction. CoRR abs/2102.09645 (2021) - [i11]Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad:
Towards Noise-adaptive, Problem-adaptive Stochastic Gradient Descent. CoRR abs/2110.11442 (2021) - 2020
- [p1]Issam H. Laradji, Reza Babanezhad:
M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning. Domain Adaptation for Visual Understanding 2020: 17-31 - [i10]Rémi Le Priol, Reza Babanezhad Harikandeh, Yoshua Bengio, Simon Lacoste-Julien:
An Analysis of the Adaptation Speed of Causal Models. CoRR abs/2005.09136 (2020) - [i9]Sharan Vaswani, Reza Babanezhad, Jose Gallego, Aaron Mishkin, Simon Lacoste-Julien, Nicolas Le Roux:
To Each Optimizer a Norm, To Each Norm its Generalization. CoRR abs/2006.06821 (2020) - [i8]Reza Babanezhad, Simon Lacoste-Julien:
Geometry-Aware Universal Mirror-Prox. CoRR abs/2011.11203 (2020)
2010 – 2019
- 2019
- [c8]Sébastien M. R. Arnold, Pierre-Antoine Manzagol, Reza Babanezhad, Ioannis Mitliagkas, Nicolas Le Roux:
Reducing the variance in online optimization by transporting past gradients. NeurIPS 2019: 5392-5403 - [i7]Ousmane Amadou Dia, Elnaz Barshan, Reza Babanezhad:
Manifold Preserving Adversarial Learning. CoRR abs/1903.03905 (2019) - [i6]Sébastien M. R. Arnold, Pierre-Antoine Manzagol, Reza Babanezhad, Ioannis Mitliagkas, Nicolas Le Roux:
Reducing the variance in online optimization by transporting past gradients. CoRR abs/1906.03532 (2019) - 2018
- [c7]Zainab Zolaktaf, Reza Babanezhad, Rachel Pottinger:
A Generic Top-N Recommendation Framework for Trading-Off Accuracy, Novelty, and Coverage. ICDE 2018: 149-160 - [c6]Nicolas Le Roux, Reza Babanezhad, Pierre-Antoine Manzagol:
Online variance-reducing optimization. ICLR (Workshop) 2018 - [c5]Reza Babanezhad, Issam H. Laradji, Alireza Shafaei, Mark Schmidt:
MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds. ECML/PKDD (2) 2018: 344-359 - [i5]Zainab Zolaktaf, Reza Babanezhad, Rachel Pottinger:
A Generic Top-N Recommendation Framework For Trading-off Accuracy, Novelty, and Coverage. CoRR abs/1803.00146 (2018) - [i4]Issam H. Laradji, Reza Babanezhad:
M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning. CoRR abs/1807.02552 (2018) - 2016
- [c4]Mohammad Emtiyaz Khan, Reza Babanezhad, Wu Lin, Mark Schmidt, Masashi Sugiyama:
Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions. UAI 2016 - 2015
- [c3]Mark Schmidt, Reza Babanezhad, Mohamed Osama Ahmed, Aaron Defazio, Ann Clifton, Anoop Sarkar:
Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields. AISTATS 2015 - [c2]Reza Babanezhad, Mohamed Osama Ahmed, Alim Virani, Mark Schmidt, Jakub Konecný, Scott Sallinen:
StopWasting My Gradients: Practical SVRG. NIPS 2015: 2251-2259 - [i3]Mark Schmidt, Reza Babanezhad, Mohamed Osama Ahmed, Aaron Defazio, Ann Clifton, Anoop Sarkar:
Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields. CoRR abs/1504.04406 (2015) - [i2]Mohammad Emtiyaz Khan, Reza Babanezhad, Wu Lin, Mark Schmidt, Masashi Sugiyama:
Convergence of Proximal-Gradient Stochastic Variational Inference under Non-Decreasing Step-Size Sequence. CoRR abs/1511.00146 (2015) - [i1]Reza Babanezhad, Mohamed Osama Ahmed, Alim Virani, Mark Schmidt, Jakub Konecný, Scott Sallinen:
Stop Wasting My Gradients: Practical SVRG. CoRR abs/1511.01942 (2015) - 2010
- [c1]Reza Babanezhad, Yusef Mehrdad Bibalan, Raman Ramsin:
Process Patterns for Web Engineering. COMPSAC 2010: 477-486
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