Anant Raj - RankMe

72 papers A* 13A 8B 1Journal 46Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Distributed Perceptron under Bounded Staleness, Partial Participation, and Noisy Communication. CoRR Keval Jain, Anant Raj, Saurav Prakash, Girish Varma
2026	J	`jnl`	Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression. CoRR Sacchit Kale, Piyushi Manupriya, Pierre Marion, Francis R. Bach, Anant Raj
2026	J	`jnl`	On the Generalization and Robustness in Conditional Value-at-Risk. CoRR Dinesh Karthik Mulumudi, Piyushi Manupriya, Gholamali Aminian, Anant Raj
2025	J	`jnl`	Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization. CoRR Chandan Tankala, Dheeraj M. Nagaraj, Anant Raj
2025	A*	`conf`	Beyond propagation of chaos: A stochastic algorithm for mean field optimization. COLT Chandan Tankala, Dheeraj Nagaraj, Anant Raj
2025	J	`jnl`	Exploring the Capabilities of the Frontier Large Language Models for Nuclear Energy Research. CoRR Ahmed Almeldein, Mohammed Alnaggar, Rick Archibald, Tom Beck, Arpan Biswas, Rike Bostelmann, Wes Brewer, Chris Bryan, Christopher Calle, Cihangir Celik, Rajni Chahal, Jong Youl Choi, Arindam Chowdhury, Mark R. Cianciosa, Franklin Curtis, Gregory G. Davidson, Sebastian De Pascuale, Lisa Fassino, Ana Gainaru, Yashika Ghai, Luke Gibson, Qian Gong, Christopher Greulich, Scott Greenwood, Cory D. Hauck, Ehab Hassan, Rinkle Juneja, Soyoung Kang, Scott Klasky, Atul Kumar, Vineet Kumar, M. Paul Laiu, Calvin Lear, Yan-Ru Lin, Jono McConnell, Furkan Oz, Rishi Pillai, Anant Raj, Pradeep Ramuhalli, Marie Romedenne, Samantha Sabatino, José Salcedo-Pérez, Nathan D. See, Arpan Sircar, Punam Thankur, Timothy Reed Younkin, Xiao-Ying Yu, Prashant Jain, Tom Evans, Prasanna Balaprakash
2025	J	`jnl`	Reweighting Improves Conditional Risk Bounds. CoRR Yikai Zhang, Jiahe Lin, Fengpei Li, Songzhu Zheng, Anant Raj, Anderson Schneider, Yuriy Nevmyvaka
2025	J	`jnl`	Reweighting Improves Conditional Risk Bounds. Trans. Mach. Learn. Res. Yikai Zhang, Jiahe Lin, Fengpei Li, Songzhu Zheng, Anant Raj, Anderson Schneider, Yuriy Nevmyvaka
2025	J	`jnl`	Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates. CoRR Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj, Csaba Szepesvári, Dale Schuurmans
2024	J	`jnl`	Deep Generative Sampling in the Dual Divergence Space: A Data-efficient & Interpretative Approach for Generative AI. CoRR Sahil Garg, Anderson Schneider, Anant Raj, Kashif Rasul, Yuriy Nevmyvaka, Sneihil Gopal, Amit Dhurandhar, Guillermo A. Cecchi, Irina Rish
2024	A*	`conf`	From Inverse Optimization to Feasibility to ERM. ICML Saurabh Mishra, Anant Raj, Sharan Vaswani
2024	J	`jnl`	From Inverse Optimization to Feasibility to ERM. CoRR Saurabh Mishra, Anant Raj, Sharan Vaswani
2024	J	`jnl`	Learning to Abstain From Uninformative Data. Trans. Mach. Learn. Res. Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen
2024	A*	`conf`	Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates. NeurIPS Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj, Csaba Szepesvári, Dale Schuurmans
2024	J	`jnl`	Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs. RLJ Michael Lu, Matin Aghaei, Anant Raj, Sharan Vaswani
2024	J	`jnl`	Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs. CoRR Michael Lu, Matin Aghaei, Anant Raj, Sharan Vaswani
2023	A*	`conf`	Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. ICML Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli
2023	J	`jnl`	Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. CoRR Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli
2023	B	`conf`	Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. ALT Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli
2023	A*	`conf`	Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. NeurIPS Anant Raj, Umut Simsekli, Alessandro Rudi
2023	J	`jnl`	Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. CoRR Anant Raj, Umut Simsekli, Alessandro Rudi
2023	A	`conf`	Explicit Regularization in Overparametrized Models via Noise Injection. AISTATS Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach
2023	J	`jnl`	Learning to Abstain From Uninformative Data. CoRR Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen
2023	J	`jnl`	Open X-Embodiment: Robotic Learning Datasets and RT-X Models. CoRR 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.
2023	A*	`conf`	Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. NeurIPS Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli
2023	J	`jnl`	Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. CoRR Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli
2023	A*	`conf`	Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms. COLT Aniket Das, Dheeraj M. Nagaraj, Anant Raj
2023	J	`jnl`	Variational Principles for Mirror Descent and Mirror Langevin Dynamics. CoRR Belinda Tzen, Anant Raj, Maxim Raginsky, Francis R. Bach
2023	J	`jnl`	Variational Principles for Mirror Descent and Mirror Langevin Dynamics. IEEE Control. Syst. Lett. Belinda Tzen, Anant Raj, Maxim Raginsky, Francis R. Bach
2022	J	`jnl`	Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. CoRR Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli
2022	J	`jnl`	Causal Feature Selection via Orthogonal Search. Trans. Mach. Learn. Res. Ashkan Soleymani, Anant Raj, Stefan Bauer, Bernhard Schölkopf, Michel Besserve
2022	A*	`conf`	Convergence of Uncertainty Sampling for Active Learning. ICML Anant Raj, Francis R. Bach
2022	J	`jnl`	Explicit Regularization in Overparametrized Models via Noise Injection. CoRR Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach
2022	A	`conf`	Faster Rates, Adaptive Algorithms, and Finite-Time Bounds for Linear Composition Optimization and Gradient TD Learning. AISTATS Anant Raj, Pooria Joulani, András György, Csaba Szepesvári
2022	J	`jnl`	MAViC: Multimodal Active Learning for Video Captioning. CoRR Gyanendra Das, Xavier Thomas, Anant Raj, Vikram Gupta
2021	J	`jnl`	Convergence of Uncertainty Sampling for Active Learning. CoRR Anant Raj, Francis R. Bach
2021	A	`conf`	Explicit Regularization of Stochastic Gradient Methods through Duality. AISTATS Anant Raj, Francis R. Bach
2020	A*	`conf`	A simpler approach to accelerated optimization: iterative averaging meets optimism. ICML Pooria Joulani, Anant Raj, András György, Csaba Szepesvári
2020	J	`jnl`	Causal Feature Selection via Orthogonal Search. CoRR Anant Raj, Stefan Bauer, Ashkan Soleymani, Michel Besserve, Bernhard Schölkopf
2020	A*	`conf`	Dual Instrumental Variable Regression. NeurIPS Krikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj
2020	J	`jnl`	Explicit Regularization of Stochastic Gradient Methods through Duality. CoRR Anant Raj, Francis R. Bach
2020	A	`conf`	Importance Sampling via Local Sensitivity. AISTATS Anant Raj, Cameron Musco, Lester Mackey
2020	J	`jnl`	Model-specific Data Subsampling with Influence Functions. CoRR Anant Raj, Cameron Musco, Lester Mackey, Nicoló Fusi
2020	J	`jnl`	Non-stationary Online Regression. CoRR Anant Raj, Pierre Gaillard, Christophe Saad
2020	A*	`conf`	Stochastic Stein Discrepancies. NeurIPS Jackson Gorham, Anant Raj, Lester Mackey
2020	J	`jnl`	Stochastic Stein Discrepancies. CoRR Jackson Gorham, Anant Raj, Lester Mackey
2019	—	`conf`	A Differentially Private Kernel Two-Sample Test. ECML/PKDD (1) Anant Raj, Ho Chung Leon Law, Dino Sejdinovic, Mijung Park
2019	J	`jnl`	Dual IV: A Single Stage Instrumental Variable Regression. CoRR Krikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj
2019	J	`jnl`	Importance Sampling via Local Sensitivity. CoRR Anant Raj, Cameron Musco, Lester Mackey
2019	J	`jnl`	Phonon dispersion using the ratio of zero-time correlations among conjugate variables: Computing full phonon dispersion surface of graphene. Comput. Phys. Commun. Anant Raj, Jacob Eapen
2019	A	`conf`	Sobolev Descent. AISTATS Youssef Mroueh, Tom Sercu, Anant Raj
2018	J	`jnl`	A Differentially Private Kernel Two-Sample Test. CoRR Anant Raj, Ho Chung Leon Law, Dino Sejdinovic, Mijung Park
2018	A*	`conf`	On Matching Pursuit and Coordinate Descent. ICML Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, Martin Jaggi
2018	J	`jnl`	Regularized Kernel and Neural Sobolev Descent: Dynamic MMD Transport. CoRR Youssef Mroueh, Tom Sercu, Anant Raj
2018	J	`jnl`	Revisiting First-Order Convex Optimization Over Linear Spaces. CoRR Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, Martin Jaggi
2018	J	`jnl`	SVRG meets SAGA: k-SVRG - A Tale of Limited Memory. CoRR Anant Raj, Sebastian U. Stich
2018	—	`conf`	Sobolev GAN. ICLR (Poster) Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng
2017	A*	`conf`	Approximate Steepest Coordinate Descent. ICML Sebastian U. Stich, Anant Raj, Martin Jaggi
2017	J	`jnl`	Approximate Steepest Coordinate Descent. CoRR Sebastian U. Stich, Anant Raj, Martin Jaggi
2017	A	`conf`	Local Group Invariant Representations via Orbit Embeddings. AISTATS Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schölkopf
2017	—	`conf`	Safe Adaptive Importance Sampling. NIPS Sebastian U. Stich, Anant Raj, Martin Jaggi
2017	J	`jnl`	Safe Adaptive Importance Sampling. CoRR Sebastian U. Stich, Anant Raj, Martin Jaggi
2017	J	`jnl`	Sobolev GAN. CoRR Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng
2016	J	`jnl`	Local Group Invariant Representations via Orbit Embeddings. CoRR Anant Raj, Abhishek Kumar, Youssef Mroueh, P. Thomas Fletcher, Bernhard Schölkopf
2016	J	`jnl`	Screening Rules for Convex Problems. CoRR Anant Raj, Jakob Olbrich, Bernd Gärtner, Bernhard Schölkopf, Martin Jaggi
2016	J	`jnl`	Unsupervised Domain Adaptation in the Wild: Dealing with Asymmetric Label Sets. CoRR Ayush Mittal, Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars
2015	J	`jnl`	Mind the Gap: Subspace based Hierarchical Domain Adaptation. CoRR Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars
2015	A	`conf`	Subspace Alignment Based Domain Adaptation for RCNN Detector. BMVC Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars
2015	J	`jnl`	Subspace Alignment Based Domain Adaptation for RCNN Detector. CoRR Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars
2014	—	`conf`	Scalable Kernel Methods via Doubly Stochastic Gradients. NIPS Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song
2014	J	`jnl`	Scalable Kernel Methods via Doubly Stochastic Gradients. CoRR Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song
2013	A	`conf`	Significance of variable height-bandwidth group delay filters in the spectral reconstruction of speech. INTERSPEECH Devanshu Arya, Anant Raj, Rajesh M. Hegde