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2020 – today
- 2024
[j5]Michael Lu, Matin Aghaei, Anant Raj, Sharan Vaswani:
Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs. RLJ 1: 216-282 (2024)- [j4]Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen:
Learning to Abstain From Uninformative Data. Trans. Mach. Learn. Res. 2024 (2024) - [c24]Saurabh Mishra, Anant Raj, Sharan Vaswani:
From Inverse Optimization to Feasibility to ERM. ICML 2024 - [i33]Saurabh Mishra, Anant Raj, Sharan Vaswani:
From Inverse Optimization to Feasibility to ERM. CoRR abs/2402.17890 (2024) - [i32]Sahil Garg, Anderson Schneider, Anant Raj, Kashif Rasul, Yuriy Nevmyvaka, Sneihil Gopal, Amit Dhurandhar, Guillermo A. Cecchi, Irina Rish:
Deep Generative Sampling in the Dual Divergence Space: A Data-efficient & Interpretative Approach for Generative AI. CoRR abs/2404.07377 (2024) - [i31]Michael Lu, Matin Aghaei, Anant Raj, Sharan Vaswani:
Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs. CoRR abs/2405.13136 (2024) - 2023
- [j3]Belinda Tzen, Anant Raj
, Maxim Raginsky, Francis R. Bach:
Variational Principles for Mirror Descent and Mirror Langevin Dynamics. IEEE Control. Syst. Lett. 7: 1542-1547 (2023) - [c23]Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach:
Explicit Regularization in Overparametrized Models via Noise Injection. AISTATS 2023: 7265-7287 - [c22]Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli:
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. ALT 2023: 1292-1342 - [c21]Aniket Das, Dheeraj M. Nagaraj, Anant Raj:
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms. COLT 2023: 4072-4129 - [c20]Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli:
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. ICML 2023: 28578-28597 - [c19]Anant Raj, Umut Simsekli, Alessandro Rudi:
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. NeurIPS 2023 - [c18]Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli:
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. NeurIPS 2023 - [i30]Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli:
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. CoRR abs/2301.11885 (2023) - [i29]Belinda Tzen, Anant Raj, Maxim Raginsky, Francis R. Bach:
Variational Principles for Mirror Descent and Mirror Langevin Dynamics. CoRR abs/2303.09532 (2023) - [i28]Anant Raj, Umut Simsekli, Alessandro Rudi:
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. CoRR abs/2303.17109 (2023) - [i27]Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli:
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. CoRR abs/2305.12056 (2023) - [i26]Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen:
Learning to Abstain From Uninformative Data. CoRR abs/2309.14240 (2023) - [i25]Open X.-Embodiment Collaboration, Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Raj, Anikait Singh, Anthony Brohan, Antonin Raffin, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Brian Ichter, Cewu Lu, Charles Xu, Chelsea Finn, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Chuer Pan, Chuyuan Fu, Coline Devin, Danny Driess, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Federico Ceola, Fei Xia, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Giulio Schiavi, Gregory Kahn, Hao Su, Haoshu Fang, Haochen Shi, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Igor Mordatch, Ilija Radosavovic, et al.:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models. CoRR abs/2310.08864 (2023) - 2022
- [j2]Ashkan Soleymani, Anant Raj, Stefan Bauer, Bernhard Schölkopf, Michel Besserve:
Causal Feature Selection via Orthogonal Search. Trans. Mach. Learn. Res. 2022 (2022) - [c17]Anant Raj, Pooria Joulani, András György, Csaba Szepesvári:
Faster Rates, Adaptive Algorithms, and Finite-Time Bounds for Linear Composition Optimization and Gradient TD Learning. AISTATS 2022: 7176-7186 - [c16]Anant Raj, Francis R. Bach:
Convergence of Uncertainty Sampling for Active Learning. ICML 2022: 18310-18331 - [i24]Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli:
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. CoRR abs/2206.01274 (2022) - [i23]Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach:
Explicit Regularization in Overparametrized Models via Noise Injection. CoRR abs/2206.04613 (2022) - [i22]Gyanendra Das, Xavier Thomas, Anant Raj, Vikram Gupta:
MAViC: Multimodal Active Learning for Video Captioning. CoRR abs/2212.11109 (2022) - 2021
- [c15]Anant Raj, Francis R. Bach:
Explicit Regularization of Stochastic Gradient Methods through Duality. AISTATS 2021: 1882-1890 - [i21]Anant Raj, Francis R. Bach:
Convergence of Uncertainty Sampling for Active Learning. CoRR abs/2110.15784 (2021) - 2020
- [c14]Anant Raj, Cameron Musco, Lester Mackey:
Importance Sampling via Local Sensitivity. AISTATS 2020: 3099-3109 - [c13]Pooria Joulani, Anant Raj, András György, Csaba Szepesvári:
A simpler approach to accelerated optimization: iterative averaging meets optimism. ICML 2020: 4984-4993 - [c12]Jackson Gorham, Anant Raj, Lester Mackey:
Stochastic Stein Discrepancies. NeurIPS 2020 - [c11]Krikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj:
Dual Instrumental Variable Regression. NeurIPS 2020 - [i20]Anant Raj, Francis R. Bach:
Explicit Regularization of Stochastic Gradient Methods through Duality. CoRR abs/2003.13807 (2020) - [i19]Jackson Gorham, Anant Raj, Lester Mackey:
Stochastic Stein Discrepancies. CoRR abs/2007.02857 (2020) - [i18]Anant Raj, Stefan Bauer, Ashkan Soleymani, Michel Besserve, Bernhard Schölkopf:
Causal Feature Selection via Orthogonal Search. CoRR abs/2007.02938 (2020) - [i17]Anant Raj, Cameron Musco, Lester Mackey, Nicoló Fusi:
Model-specific Data Subsampling with Influence Functions. CoRR abs/2010.10218 (2020) - [i16]Anant Raj, Pierre Gaillard, Christophe Saad:
Non-stationary Online Regression. CoRR abs/2011.06957 (2020)
2010 – 2019
- 2019
- [j1]Anant Raj, Jacob Eapen:
Phonon dispersion using the ratio of zero-time correlations among conjugate variables: Computing full phonon dispersion surface of graphene. Comput. Phys. Commun. 238: 124-137 (2019) - [c10]Youssef Mroueh, Tom Sercu, Anant Raj:
Sobolev Descent. AISTATS 2019: 2976-2985 - [c9]Anant Raj, Ho Chung Leon Law, Dino Sejdinovic, Mijung Park:
A Differentially Private Kernel Two-Sample Test. ECML/PKDD (1) 2019: 697-724 - [i15]Krikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj:
Dual IV: A Single Stage Instrumental Variable Regression. CoRR abs/1910.12358 (2019) - [i14]Anant Raj, Cameron Musco, Lester Mackey:
Importance Sampling via Local Sensitivity. CoRR abs/1911.01575 (2019) - 2018
- [c8]Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng:
Sobolev GAN. ICLR (Poster) 2018 - [c7]Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, Martin Jaggi:
On Matching Pursuit and Coordinate Descent. ICML 2018: 3204-3213 - [i13]Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, Martin Jaggi:
Revisiting First-Order Convex Optimization Over Linear Spaces. CoRR abs/1803.09539 (2018) - [i12]Anant Raj, Sebastian U. Stich:
SVRG meets SAGA: k-SVRG - A Tale of Limited Memory. CoRR abs/1805.00982 (2018) - [i11]Youssef Mroueh, Tom Sercu, Anant Raj:
Regularized Kernel and Neural Sobolev Descent: Dynamic MMD Transport. CoRR abs/1805.12062 (2018) - [i10]Anant Raj, Ho Chung Leon Law, Dino Sejdinovic, Mijung Park:
A Differentially Private Kernel Two-Sample Test. CoRR abs/1808.00380 (2018) - 2017
- [c6]Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schölkopf:
Local Group Invariant Representations via Orbit Embeddings. AISTATS 2017: 1225-1235 - [c5]Sebastian U. Stich, Anant Raj, Martin Jaggi:
Approximate Steepest Coordinate Descent. ICML 2017: 3251-3259 - [c4]Sebastian U. Stich, Anant Raj, Martin Jaggi:
Safe Adaptive Importance Sampling. NIPS 2017: 4381-4391 - [i9]Sebastian U. Stich, Anant Raj, Martin Jaggi:
Approximate Steepest Coordinate Descent. CoRR abs/1706.08427 (2017) - [i8]Sebastian U. Stich, Anant Raj, Martin Jaggi:
Safe Adaptive Importance Sampling. CoRR abs/1711.02637 (2017) - [i7]Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng:
Sobolev GAN. CoRR abs/1711.04894 (2017) - 2016
- [i6]Ayush Mittal, Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars:
Unsupervised Domain Adaptation in the Wild: Dealing with Asymmetric Label Sets. CoRR abs/1603.08105 (2016) - [i5]Anant Raj, Jakob Olbrich, Bernd Gärtner, Bernhard Schölkopf, Martin Jaggi:
Screening Rules for Convex Problems. CoRR abs/1609.07478 (2016) - [i4]Anant Raj, Abhishek Kumar, Youssef Mroueh, P. Thomas Fletcher, Bernhard Schölkopf:
Local Group Invariant Representations via Orbit Embeddings. CoRR abs/1612.01988 (2016) - 2015
- [c3]Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars:
Subspace Alignment Based Domain Adaptation for RCNN Detector. BMVC 2015: 166.1-166.11 - [i3]Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars:
Mind the Gap: Subspace based Hierarchical Domain Adaptation. CoRR abs/1501.03952 (2015) - [i2]Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars:
Subspace Alignment Based Domain Adaptation for RCNN Detector. CoRR abs/1507.05578 (2015) - 2014
- [c2]Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song:
Scalable Kernel Methods via Doubly Stochastic Gradients. NIPS 2014: 3041-3049 - [i1]Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song:
Scalable Kernel Methods via Doubly Stochastic Gradients. CoRR abs/1407.5599 (2014) - 2013
- [c1]Devanshu Arya, Anant Raj, Rajesh M. Hegde:
Significance of variable height-bandwidth group delay filters in the spectral reconstruction of speech. INTERSPEECH 2013: 1682-1686
Coauthor Index
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