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2020 – today
- 2023
[j60]Thomas Pethick, Grigorios Chrysos, Volkan Cevher:
Revisiting adversarial training for the worst-performing class. Trans. Mach. Learn. Res. 2023 (2023)- [c183]Junaid Ali
, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell:
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. AIES 2023: 809-833 - [c182]Grigorios G. Chrysos, Bohan Wang, Jiankang Deng, Volkan Cevher:
Regularization of polynomial networks for image recognition. CVPR 2023: 16123-16132 - [c181]Fabian Latorre, Igor Krawczuk, Leello Tadesse Dadi, Thomas Pethick, Volkan Cevher:
Finding Actual Descent Directions for Adversarial Training. ICLR 2023 - [c180]Thomas Pethick, Olivier Fercoq, Puya Latafat, Panagiotis Patrinos, Volkan Cevher:
Solving stochastic weak Minty variational inequalities without increasing batch size. ICLR 2023 - [c179]Ali Ramezani-Kebrya, Kimon Antonakopoulos, Igor Krawczuk, Justin Deschenaux, Volkan Cevher:
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees. ICLR 2023 - [c178]Clément Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard:
DiGress: Discrete Denoising diffusion for graph generation. ICLR 2023 - [c177]Fanghui Liu, Luca Viano, Volkan Cevher:
What can online reinforcement learning with function approximation benefit from general coverage conditions? ICML 2023: 22063-22091 - [c176]Ioannis Panageas, Stratis Skoulakis, Luca Viano, Xiao Wang, Volkan Cevher:
Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees. ICML 2023: 26904-26930 - [c175]Harvineet Singh, Matthäus Kleindessner, Volkan Cevher, Rumi Chunara, Chris Russell:
When do Minimax-fair Learning and Empirical Risk Minimization Coincide? ICML 2023: 31969-31989 - [c174]Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Francesco Locatello, Volkan Cevher:
Benign Overfitting in Deep Neural Networks under Lazy Training. ICML 2023: 43105-43128 - [c173]Volkan Cevher, Georgios Piliouras, Ryann Sim, Stratis Skoulakis:
Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps. SOSA 2023: 192-206 - [i124]Volkan Cevher, Georgios Piliouras, Ryann Sim, Stratis Skoulakis:
Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps. CoRR abs/2301.03931 (2023) - [i123]Thomas Pethick, Grigorios G. Chrysos, Volkan Cevher:
Revisiting adversarial training for the worst-performing class. CoRR abs/2302.08872 (2023) - [i122]Thomas Pethick, Olivier Fercoq, Puya Latafat, Panagiotis Patrinos, Volkan Cevher:
Solving stochastic weak Minty variational inequalities without increasing batch size. CoRR abs/2302.09029 (2023) - [i121]Thomas Pethick, Puya Latafat, Panagiotis Patrinos, Olivier Fercoq, Volkan Cevher:
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems. CoRR abs/2302.09831 (2023) - [i120]Grigorios G. Chrysos, Bohan Wang, Jiankang Deng, Volkan Cevher:
Regularization of polynomial networks for image recognition. CoRR abs/2303.13896 (2023) - [i119]Fanghui Liu, Luca Viano, Volkan Cevher:
Provable benefits of general coverage conditions in efficient online RL with function approximation. CoRR abs/2304.12886 (2023) - [i118]Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Francesco Locatello, Volkan Cevher:
Benign Overfitting in Deep Neural Networks under Lazy Training. CoRR abs/2305.19377 (2023) - [i117]Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher:
Federated Learning under Covariate Shifts with Generalization Guarantees. CoRR abs/2306.05325 (2023) - [i116]Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher:
Adversarial Training Should Be Cast as a Non-Zero-Sum Game. CoRR abs/2306.11035 (2023) - [i115]Ioannis Panageas, Stratis Skoulakis, Luca Viano, Xiao Wang, Volkan Cevher:
Semi Bandit Dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees. CoRR abs/2306.15543 (2023) - [i114]Ali Ramezani-Kebrya, Kimon Antonakopoulos, Igor Krawczuk, Justin Deschenaux, Volkan Cevher:
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees. CoRR abs/2308.09187 (2023) - [i113]Ioannis Panageas, Nikolas Patris, Stratis Skoulakis, Volkan Cevher:
Exponential Lower Bounds for Fictitious Play in Potential Games. CoRR abs/2310.02387 (2023) - [i112]Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell:
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. CoRR abs/2310.11867 (2023) - [i111]Thomas Pethick, Wanyun Xie, Volkan Cevher:
Stable Nonconvex-Nonconcave Training via Linear Interpolation. CoRR abs/2310.13459 (2023) - [i110]Zhenyu Zhu, Francesco Locatello, Volkan Cevher:
Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling. CoRR abs/2310.18123 (2023) - [i109]Lorenzo Brusca, Lars C. P. M. Quaedvlieg, Stratis Skoulakis, Grigorios G. Chrysos, Volkan Cevher:
Maximum Independent Set: Self-Training through Dynamic Programming. CoRR abs/2310.18672 (2023) - [i108]Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher:
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. CoRR abs/2310.20579 (2023) - [i107]Yongtao Wu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher:
On the Convergence of Encoder-only Shallow Transformers. CoRR abs/2311.01575 (2023) - 2022
- [j59]Deyi Liu, Volkan Cevher, Quoc Tran-Dinh:
A Newton Frank-Wolfe method for constrained self-concordant minimization. J. Glob. Optim. 83(2): 273-299 (2022) - [j58]Arda Uran, Kerim Türe, Cosimo Aprile, Alix Trouillet, Florian Fallegger, Emilie C. M. Revol, Azita Emami, Stéphanie P. Lacour, Catherine Dehollain, Yusuf Leblebici, Volkan Cevher:
A 16-Channel Neural Recording System-on-Chip With CHT Feature Extraction Processor in 65-nm CMOS. IEEE J. Solid State Circuits 57(9): 2752-2763 (2022) - [j57]Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher:
On the Convergence of Stochastic Primal-Dual Hybrid Gradient. SIAM J. Optim. 32(2): 1288-1318 (2022) - [c172]Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever:
Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. AISTATS 2022: 8439-8457 - [c171]Moulik Choraria, Leello Tadesse Dadi, Grigorios Chrysos, Julien Mairal, Volkan Cevher:
The Spectral Bias of Polynomial Neural Networks. ICLR 2022 - [c170]Ali Kavis, Kfir Yehuda Levy, Volkan Cevher:
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize. ICLR 2022 - [c169]Thomas Pethick, Puya Latafat, Panos Patrinos, Olivier Fercoq, Volkan Cevher:
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems. ICLR 2022 - [c168]Zhenyu Zhu, Fabian Latorre, Grigorios Chrysos, Volkan Cevher:
Controlling the Complexity and Lipschitz Constant improves Polynomial Nets. ICLR 2022 - [c167]Ahmet Alacaoglu, Luca Viano, Niao He, Volkan Cevher:
A Natural Actor-Critic Framework for Zero-Sum Markov Games. ICML 2022: 307-366 - [c166]Kimon Antonakopoulos, Dong Quan Vu, Volkan Cevher, Kfir Y. Levy, Panayotis Mertikopoulos:
UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees. ICML 2022: 772-795 - [c165]Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Dominik Janzing, Bernhard Schölkopf, Francesco Locatello:
Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. ICML 2022: 18741-18753 - [c164]Fanghui Liu, Johan A. K. Suykens, Volkan Cevher:
On the Double Descent of Random Features Models Trained with SGD. NeurIPS 2022 - [c163]Fanghui Liu, Luca Viano, Volkan Cevher:
Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration. NeurIPS 2022 - [c162]Elías Abad-Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher:
Sound and Complete Verification of Polynomial Networks. NeurIPS 2022 - [c161]Kimon Antonakopoulos, Ali Kavis, Volkan Cevher:
Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods. NeurIPS 2022 - [c160]Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos:
No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation. NeurIPS 2022 - [c159]Ali Kavis, Stratis Skoulakis, Kimon Antonakopoulos, Leello Tadesse Dadi, Volkan Cevher:
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization. NeurIPS 2022 - [c158]Paul Rolland, Luca Viano, Norman Schürhoff, Boris Nikolov, Volkan Cevher:
Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning. NeurIPS 2022 - [c157]Luca Viano, Angeliki Kamoutsi, Gergely Neu, Igor Krawczuk, Volkan Cevher:
Proximal Point Imitation Learning. NeurIPS 2022 - [c156]Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher:
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study. NeurIPS 2022 - [c155]Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher:
Generalization Properties of NAS under Activation and Skip Connection Search. NeurIPS 2022 - [c154]Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher:
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization). NeurIPS 2022 - [i106]Ahmet Alacaoglu, Volkan Cevher, Stephen J. Wright:
On the Complexity of a Practical Primal-Dual Coordinate Method. CoRR abs/2201.07684 (2022) - [i105]Zhenyu Zhu, Fabian Latorre, Grigorios G. Chrysos, Volkan Cevher:
Controlling the Complexity and Lipschitz Constant improves polynomial nets. CoRR abs/2202.05068 (2022) - [i104]Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever:
Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. CoRR abs/2202.13212 (2022) - [i103]Moulik Choraria, Leello Tadesse Dadi, Grigorios Chrysos, Julien Mairal, Volkan Cevher:
The Spectral Bias of Polynomial Neural Networks. CoRR abs/2202.13473 (2022) - [i102]Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Bernhard Schölkopf, Dominik Janzing, Francesco Locatello:
Score matching enables causal discovery of nonlinear additive noise models. CoRR abs/2203.04413 (2022) - [i101]Ali Kavis, Kfir Yehuda Levy, Volkan Cevher:
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize. CoRR abs/2204.02833 (2022) - [i100]Panayotis Mertikopoulos, Ya-Ping Hsieh, Volkan Cevher:
Learning in games from a stochastic approximation viewpoint. CoRR abs/2206.03922 (2022) - [i99]Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos:
No-Regret Learning in Games with Noisy Feedback: Faster Rates and Adaptivity via Learning Rate Separation. CoRR abs/2206.06015 (2022) - [i98]Yongtao Wu, Grigorios G. Chrysos, Volkan Cevher:
Adversarial Audio Synthesis with Complex-valued Polynomial Networks. CoRR abs/2206.06811 (2022) - [i97]Elías Abad-Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher:
Sound and Complete Verification of Polynomial Networks. CoRR abs/2209.07235 (2022) - [i96]Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher:
Generalization Properties of NAS under Activation and Skip Connection Search. CoRR abs/2209.07238 (2022) - [i95]Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher:
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization). CoRR abs/2209.07263 (2022) - [i94]Fanghui Liu, Luca Viano, Volkan Cevher:
Understanding Deep Neural Function Approximation in Reinforcement Learning via ε-Greedy Exploration. CoRR abs/2209.07376 (2022) - [i93]Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher:
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study. CoRR abs/2209.07736 (2022) - [i92]Luca Viano, Angeliki Kamoutsi, Gergely Neu, Igor Krawczuk, Volkan Cevher:
Proximal Point Imitation Learning. CoRR abs/2209.10968 (2022) - [i91]Paul Rolland, Luca Viano, Norman Schürhoff, Boris Nikolov, Volkan Cevher:
Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning. CoRR abs/2209.10974 (2022) - [i90]Clément Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard:
DiGress: Discrete Denoising diffusion for graph generation. CoRR abs/2209.14734 (2022) - [i89]Kimon Antonakopoulos, Ali Kavis, Volkan Cevher:
Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods. CoRR abs/2211.01832 (2022) - [i88]Ali Kavis, Stratis Skoulakis, Kimon Antonakopoulos, Leello Tadesse Dadi, Volkan Cevher:
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization. CoRR abs/2211.01851 (2022) - 2021
- [j56]Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher:
Forward-reflected-backward method with variance reduction. Comput. Optim. Appl. 80(2): 321-346 (2021) - [j55]Lijun Ding, Alp Yurtsever, Volkan Cevher, Joel A. Tropp, Madeleine Udell:
An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity. SIAM J. Optim. 31(4): 2695-2725 (2021) - [j54]Alp Yurtsever, Joel A. Tropp, Olivier Fercoq, Madeleine Udell, Volkan Cevher:
Scalable Semidefinite Programming. SIAM J. Math. Data Sci. 3(1): 171-200 (2021) - [c153]Arda Uran, Kerim Türe, Cosimo Aprile, Alix Trouillet, Florian Fallegger, Azita Emami, Stéphanie P. Lacour, Catherine Dehollain, Yusuf Leblebici, Volkan Cevher:
A 16-Channel Wireless Neural Recording System-on-Chip with CHT Feature Extraction Processor in 65nm CMOS. CICC 2021: 1-2 - [c152]Zhaodong Sun, Fabian Latorre, Thomas Sanchez, Volkan Cevher:
A Plug-and-Play Deep Image Prior. ICASSP 2021: 8103-8107 - [c151]Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher:
Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach. ICML 2021: 4008-4017 - [c150]Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher:
The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets. ICML 2021: 4337-4348 - [c149]Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher:
A first-order primal-dual method with adaptivity to local smoothness. NeurIPS 2021: 6171-6182 - [c148]Chaehwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin Eftekhari, Volkan Cevher:
Subquadratic Overparameterization for Shallow Neural Networks. NeurIPS 2021: 11247-11259 - [c147]Kimon Antonakopoulos, Thomas Pethick, Ali Kavis, Panayotis Mertikopoulos, Volkan Cevher:
Sifting through the noise: Universal first-order methods for stochastic variational inequalities. NeurIPS 2021: 13099-13111 - [c146]Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher:
Convergence of adaptive algorithms for constrained weakly convex optimization. NeurIPS 2021: 14214-14225 - [c145]Kfir Y. Levy, Ali Kavis, Volkan Cevher:
STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization. NeurIPS 2021: 20571-20582 - [c144]Fabian Latorre, Leello Tadesse Dadi, Paul Rolland, Volkan Cevher:
The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers. NeurIPS 2021: 21138-21149 - [c143]Luca Viano, Yu-Ting Huang, Parameswaran Kamalaruban, Adrian Weller, Volkan Cevher:
Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch. NeurIPS 2021: 25917-25931 - [i87]Aleksandr Timofeev, Grigorios G. Chrysos, Volkan Cevher:
Self-Supervised Neural Architecture Search for Imbalanced Datasets. CoRR abs/2109.08580 (2021) - [i86]Fanghui Liu, Johan A. K. Suykens, Volkan Cevher:
On the Double Descent of Random Features Models Trained with SGD. CoRR abs/2110.06910 (2021) - [i85]Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher:
A first-order primal-dual method with adaptivity to local smoothness. CoRR abs/2110.15148 (2021) - [i84]Kfir Y. Levy, Ali Kavis, Volkan Cevher:
STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization. CoRR abs/2111.01040 (2021) - [i83]Chaehwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin Eftekhari, Volkan Cevher:
Subquadratic Overparameterization for Shallow Neural Networks. CoRR abs/2111.01875 (2021) - 2020
- [j53]Junhong Lin, Volkan Cevher:
Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections. J. Mach. Learn. Res. 21: 20:1-20:44 (2020) - [j52]Junhong Lin, Volkan Cevher:
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms. J. Mach. Learn. Res. 21: 147:1-147:63 (2020) - [j51]Quoc Tran-Dinh, Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher:
An adaptive primal-dual framework for nonsmooth convex minimization. Math. Program. Comput. 12(3): 451-491 (2020) - [j50]Waheed U. Bajwa, Volkan Cevher, Dimitris S. Papailiopoulos, Anna Scaglione:
Machine Learning From Distributed, Streaming Data [From the Guest Editors]. IEEE Signal Process. Mag. 37(3): 11-13 (2020) - [j49]Donghwan Lee, Niao He, Parameswaran Kamalaruban, Volkan Cevher:
Optimization for Reinforcement Learning: From a single agent to cooperative agents. IEEE Signal Process. Mag. 37(3): 123-135 (2020) - [c142]Thomas Sanchez, Baran Gözcü, Ruud B. van Heeswijk, Armin Eftekhari, Efe Ilicak, Tolga Çukur, Volkan Cevher:
Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI. ICASSP 2020: 8584-8588 - [c141]Fabian Latorre Gómez, Paul Rolland, Volkan Cevher:
Lipschitz constant estimation of Neural Networks via sparse polynomial optimization. ICLR 2020 - [c140]Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher:
Random extrapolation for primal-dual coordinate descent. ICML 2020: 191-201 - [c139]Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher:
A new regret analysis for Adam-type algorithms. ICML 2020: 202-210 - [c138]Fabian Latorre Gómez, Paul Rolland, Nadav Hallak, Volkan Cevher:
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks. ICML 2020: 5651-5661 - [c137]Paul Rolland, Armin Eftekhari, Ali Kavis, Volkan Cevher:
Double-Loop Unadjusted Langevin Algorithm. ICML 2020: 8169-8177 - [c136]Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher:
Conditional gradient methods for stochastically constrained convex minimization. ICML 2020: 9775-9785 - [c135]Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi, Volkan Cevher:
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics. NeurIPS 2020 - [c134]Panayotis Mertikopoulos, Nadav Hallak, Ali Kavis, Volkan Cevher:
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems. NeurIPS 2020 - [i82]Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi, Volkan Cevher:
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics. CoRR abs/2002.06063 (2020) - [i81]Deyi Liu, Volkan Cevher, Quoc Tran-Dinh:
A Newton Frank-Wolfe Method for Constrained Self-Concordant Minimization. CoRR abs/2002.07003 (2020) - [i80]Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher:
A new regret analysis for Adam-type algorithms. CoRR abs/2003.09729 (2020) - [i79]Fabian Latorre Gómez, Paul Rolland, Volkan Cevher:
Lipschitz constant estimation of Neural Networks via sparse polynomial optimization. CoRR abs/2004.08688 (2020) - [i78]Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher:
Convergence of adaptive algorithms for weakly convex constrained optimization. CoRR abs/2006.06650 (2020) - [i77]Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher:
The limits of min-max optimization algorithms: convergence to spurious non-critical sets. CoRR abs/2006.09065 (2020) - [i76]Panayotis Mertikopoulos, Nadav Hallak, Ali Kavis, Volkan Cevher:
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems. CoRR abs/2006.11144 (2020) - [i75]Parameswaran Kamalaruban, Rati Devidze, Volkan Cevher, Adish Singla:
Environment Shaping in Reinforcement Learning using State Abstraction. CoRR abs/2006.13160 (2020) - [i74]Martin Troussard, Emmanuel Pignat, Parameswaran Kamalaruban, Sylvain Calinon, Volkan Cevher:
Interaction-limited Inverse Reinforcement Learning. CoRR abs/2007.00425 (2020) - [i73]Fabian Latorre Gómez, Paul Rolland, Nadav Hallak, Volkan Cevher:
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks. CoRR abs/2007.01003 (2020) - [i72]Paul Rolland, Armin Eftekhari, Ali Kavis, Volkan Cevher:
Double-Loop Unadjusted Langevin Algorithm. CoRR abs/2007.01147 (2020) - [i71]Luca Viano,