Sanjay Shakkottai

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 147

Top Venues

CoRR

ICML

NeurIPS

IEEE/ACM Trans. Netw.

Publications

Litu Rout, Yujia Chen, Nataniel Ruiz, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu
RB-Modulation: Training-Free Personalization of Diffusion Models using Stochastic Optimal Control. CoRR (2024)
Arghyadip Roy, Sanjay Shakkottai, R. Srikant
Adaptive KL-UCB Based Bandit Algorithms for Markovian and I.I.D. Settings. IEEE Trans. Autom. Control. 69 (4) (2024)
Liam Collins, Advait Parulekar, Aryan Mokhtari, Sujay Sanghavi, Sanjay Shakkottai
In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness. CoRR (2024)
Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alex Dimakis, Sanjay Shakkottai
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models. NeurIPS (2023)
Litu Rout, Advait Parulekar, Constantine Caramanis, Sanjay Shakkottai
A Theoretical Justification for Image Inpainting using Denoising Diffusion Probabilistic Models. CoRR (2023)
Matthew Faw, Litu Rout, Constantine Caramanis, Sanjay Shakkottai
Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD. CoRR (2023)
Litu Rout, Yujia Chen, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu
Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion. CoRR (2023)
Daniel Vial, Sanjay Shakkottai, R. Srikant
Robust Multi-Agent Bandits Over Undirected Graphs. SIGMETRICS (Abstracts) (2023)
Matthew Faw, Litu Rout, Constantine Caramanis, Sanjay Shakkottai
Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD. COLT (2023)
Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alexandros G. Dimakis, Sanjay Shakkottai
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models. CoRR (2023)
Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi, Aryan Mokhtari, Sanjay Shakkottai
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks. CoRR (2023)
Ronshee Chawla, Daniel Vial, Sanjay Shakkottai, R. Srikant
Collaborative Multi-Agent Heterogeneous Multi-Armed Bandits. CoRR (2023)
Ronshee Chawla, Abishek Sankararaman, Sanjay Shakkottai
Multiagent Low-Dimensional Linear Bandits. IEEE Trans. Autom. Control. 68 (5) (2023)
Advait U. Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai
PAC Generalization via Invariant Representations. ICML (2023)
Advait Parulekar, Liam Collins, Karthikeyan Shanmugam, Aryan Mokhtari, Sanjay Shakkottai
InfoNCE Loss Provably Learns Cluster-Preserving Representations. COLT (2023)
Ronshee Chawla, Daniel Vial, Sanjay Shakkottai, R. Srikant
Collaborative Multi-Agent Heterogeneous Multi-Armed Bandits. ICML (2023)
Jiayi Chen, Nihal Sharma, Tarannum Khan, Shu Liu, Brian Chang, Aditya Akella, Sanjay Shakkottai, Ramesh K. Sitaraman
Darwin: Flexible Learning-based CDN Caching. SIGCOMM (2023)
Jerry Gu, Liam Collins, Debashri Roy, Aryan Mokhtari, Sanjay Shakkottai, Kaushik R. Chowdhury
Meta-Learning for Image-Guided Millimeter-Wave Beam Selection in Unseen Environments. ICASSP (2023)
Advait Parulekar, Liam Collins, Karthikeyan Shanmugam, Aryan Mokhtari, Sanjay Shakkottai
InfoNCE Loss Provably Learns Cluster-Preserving Representations. CoRR (2023)
Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel Ward
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. COLT (2022)
Liam Collins, Aryan Mokhtari, Sanjay Shakkottai
How Does the Task Landscape Affect MAML Performance? CoLLAs (2022)
Advait Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai
PAC Generalization via Invariant Representations. CoRR (2022)
Daniel Vial, Advait Parulekar, Sanjay Shakkottai, R. Srikant
Improved Algorithms for Misspecified Linear Markov Decision Processes. AISTATS (2022)
Daniel Vial, Sanjay Shakkottai, R. Srikant
Robust Multi-Agent Bandits Over Undirected Graphs. CoRR (2022)
Matthew Faw, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Learning To Maximize Welfare with a Reusable Resource. Proc. ACM Meas. Anal. Comput. Syst. 6 (2) (2022)
Daniel Vial, Advait Parulekar, Sanjay Shakkottai, R. Srikant
Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation. ICML (2022)
Daniel Vial, Sujay Sanghavi, Sanjay Shakkottai, R. Srikant
Minimax Regret for Cascading Bandits. NeurIPS (2022)
Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai
Asymptotically-Optimal Gaussian Bandits with Side Observations. ICML (2022)
Liam Collins, Aryan Mokhtari, Sewoong Oh, Sanjay Shakkottai
MAML and ANIL Provably Learn Representations. CoRR (2022)
Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel Ward
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. CoRR (2022)
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning. NeurIPS (2022)
Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret. CoRR (2022)
Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret. NeurIPS (2022)
Matthew Faw, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Learning To Maximize Welfare with a Reusable Resource. SIGMETRICS (Abstracts) (2022)
Dawei Sun, Negin Musavi, Geir E. Dullerud, Sanjay Shakkottai, Sayan Mitra
Learning Certifiably Robust Controllers Using Fragile Perception. CoRR (2022)
Jianhan Song, Gustavo de Veciana, Sanjay Shakkottai
Online learning for multi-agent based resource allocation in weakly coupled wireless systems. MobiHoc (2022)
Isfar Tariq, Kartik Patel, Thomas David Novlan, Salam Akoum, Milap Majmundar, Gustavo de Veciana, Sanjay Shakkottai
Bandit Learning-based Online User Clustering and Selection for Cellular Networks. WiOpt (2022)
Liam Collins, Aryan Mokhtari, Sewoong Oh, Sanjay Shakkottai
MAML and ANIL Provably Learn Representations. ICML (2022)
Daniel Vial, Sujay Sanghavi, Sanjay Shakkottai, R. Srikant
Minimax Regret for Cascading Bandits. CoRR (2022)
Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. Chowdhury, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC (2022)
Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
Linear Bandit Algorithms with Sublinear Time Complexity. ICML (2022)
Jianhan Song, Gustavo de Veciana, Sanjay Shakkottai
Online Learning for Hierarchical Scheduling to Support Network Slicing in Cellular Networks. SIGMETRICS Perform. Evaluation Rev. 49 (3) (2022)
Jianhan Song, Gustavo de Veciana, Sanjay Shakkottai
Meta-Scheduling for the Wireless Downlink Through Learning With Bandit Feedback. IEEE/ACM Trans. Netw. 30 (2) (2022)
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning. CoRR (2022)
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai
Combinatorial Blocking Bandits with Stochastic Delays. ICML (2021)
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
Exploiting Shared Representations for Personalized Federated Learning. CoRR (2021)
Steven Gutstein, Brent Lance, Sanjay Shakkottai
Does Optimal Source Task Performance Imply Optimal Pre-training for a Target Task? CoRR (2021)
Jianhan Song, Gustavo de Veciana, Sanjay Shakkottai
Online learning for hierarchical scheduling to support network slicing in cellular networks. Perform. Evaluation 152 (2021)
Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, Sanjay Shakkottai
Job Dispatching Policies for Queueing Systems with Unknown Service Rates. MobiHoc (2021)
Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. CoRR (2021)
Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants. CoRR (2021)
Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, Sanjay Shakkottai
Job Dispatching Policies for Queueing Systems with Unknown Service Rates. CoRR (2021)
Daniel Vial, Sanjay Shakkottai, R. Srikant
Robust Multi-Agent Multi-Armed Bandits. MobiHoc (2021)
Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. NeurIPS (2021)
Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
Linear Bandit Algorithms with Sublinear Time Complexity. CoRR (2021)
Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Contextual Blocking Bandits. AISTATS (2021)
Daniel Vial, Sanjay Shakkottai, R. Srikant
Robust Multi-Agent Bandits Over Undirected Graphs. Proc. ACM Meas. Anal. Comput. Syst. 6 (3) (2021)
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai
Combinatorial Blocking Bandits with Stochastic Delays. CoRR (2021)
Daniel Vial, Advait Parulekar, Sanjay Shakkottai, R. Srikant
Improved Algorithms for Misspecified Linear Markov Decision Processes. CoRR (2021)
Negin Musavi, Dawei Sun, Sayan Mitra, Geir E. Dullerud, Sanjay Shakkottai
HooVer: A Framework for Verification and Parameter Synthesis in Stochastic Systems using Optimistic Optimization. CCTA (2021)
Yi Zhang, Soumya Basu, Sanjay Shakkottai, Robert W. Heath Jr.
MmWave Codebook Selection in Rapidly-Varying Channels via Multinomial Thompson Sampling. MobiHoc (2021)
Subhashini Krishnasamy, Rajat Sen, Ramesh Johari, Sanjay Shakkottai
Learning Unknown Service Rates in Queues: A Multiarmed Bandit Approach. Oper. Res. 69 (1) (2021)
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
Exploiting Shared Representations for Personalized Federated Learning. ICML (2021)
Daniel Vial, Advait Parulekar, Sanjay Shakkottai, R. Srikant
Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation. CoRR (2021)
Isfar Tariq, Rajat Sen, Thomas David Novlan, Salam Akoum, Milap Majmundar, Gustavo de Veciana, Sanjay Shakkottai
Auto-Tuning for Cellular Scheduling Through Bandit-Learning and Low-Dimensional Clustering. IEEE/ACM Trans. Netw. 29 (5) (2021)
Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai
Episodic Bandits with Stochastic Experts. CoRR (2021)
Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Contextual Blocking Bandits. CoRR (2020)
Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. NeurIPS (2020)
Jianhan Song, Gustavo de Veciana, Sanjay Shakkottai
Meta-Scheduling for the Wireless Downlink through Learning with Bandit Feedback. WiOpt (2020)
Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes. CoRR (2020)
Daniel Vial, Sanjay Shakkottai, R. Srikant
Robust Multi-Agent Multi-Armed Bandits. CoRR (2020)
Abishek Sankararaman, Ayalvadi Ganesh, Sanjay Shakkottai
Social Learning in Multi Agent Multi Armed Bandits. SIGMETRICS (Abstracts) (2020)
Liam Collins, Aryan Mokhtari, Sanjay Shakkottai
Task-Robust Model-Agnostic Meta-Learning. NeurIPS (2020)
Daniel Vial, Sanjay Shakkottai, R. Srikant
One-bit feedback is sufficient for upper confidence bound policies. CoRR (2020)
Advait Parulekar, Soumya Basu, Aditya Gopalan, Karthikeyan Shanmugam, Sanjay Shakkottai
Stochastic Linear Bandits with Protected Subspace. CoRR (2020)
Ronshee Chawla, Abishek Sankararaman, Ayalvadi Ganesh, Sanjay Shakkottai
The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits. CoRR (2020)
Ronshee Chawla, Abishek Sankararaman, Ayalvadi Ganesh, Sanjay Shakkottai
The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits. AISTATS (2020)
Ronshee Chawla, Abishek Sankararaman, Sanjay Shakkottai
Multi-Agent Low-Dimensional Linear Bandits. CoRR (2020)
Liam Collins, Aryan Mokhtari, Sanjay Shakkottai
Distribution-Agnostic Model-Agnostic Meta-Learning. CoRR (2020)
Arghyadip Roy, Sanjay Shakkottai, R. Srikant
Hellinger KL-UCB based Bandit Algorithms for Markovian and i.i.d. Settings. CoRR (2020)
Arjun Anand, Gustavo de Veciana, Sanjay Shakkottai
Joint Scheduling of URLLC and eMBB Traffic in 5G Wireless Networks. IEEE/ACM Trans. Netw. 28 (2) (2020)
Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai
Warm Starting Bandits with Side Information from Confounded Data. CoRR (2020)
Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes. NeurIPS (2020)
Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath
Applications of Common Entropy for Causal Inference. NeurIPS (2020)
Liam Collins, Aryan Mokhtari, Sanjay Shakkottai
Why Does MAML Outperform ERM? An Optimization Perspective. CoRR (2020)
Yi Zhang, Kartik Patel, Sanjay Shakkottai, Robert W. Heath Jr.
Side-information-aided Noncoherent Beam Alignment Design for Millimeter Wave Systems. MobiHoc (2019)
Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai
Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach. AISTATS (2019)
Soumya Basu, Sanjay Shakkottai
Switching Constrained Max-Weight Scheduling for Wireless Networks. INFOCOM (2019)
Negin Musavi, Dawei Sun, Sayan Mitra, Geir E. Dullerud, Sanjay Shakkottai
Optimistic Optimization for Statistical Model Checking with Regret Bounds. CoRR (2019)
Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. CoRR (2019)
Abishek Sankararaman, Ayalvadi Ganesh, Sanjay Shakkottai
Social Learning in Multi Agent Multi Armed Bandits. CoRR (2019)
Abishek Sankararaman, Ayalvadi Ganesh, Sanjay Shakkottai
Social Learning in Multi Agent Multi Armed Bandits. Proc. ACM Meas. Anal. Comput. Syst. 3 (3) (2019)
Isfar Tariq, Rajat Sen, Gustavo de Veciana, Sanjay Shakkottai
Online Channel-state Clustering And Multiuser Capacity Learning For Wireless Scheduling. INFOCOM (2019)
Maurice Diesendruck, Ethan R. Elenberg, Rajat Sen, Guy W. Cole, Sanjay Shakkottai, Sinead A. Williamson
Importance Weighted Generative Networks. ECML/PKDD (2) (2019)
Soumya Basu, Steven Gutstein, Brent Lance, Sanjay Shakkottai
Pareto Optimal Streaming Unsupervised Classification. ICML (2019)
Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai
Blocking Bandits. CoRR (2019)
Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai
Blocking Bandits. NeurIPS (2019)
Subhashini Krishnasamy, P. T. Akhil, Ari Arapostathis, Rajesh Sundaresan, Sanjay Shakkottai
Augmenting Max-Weight With Explicit Learning for Wireless Scheduling With Switching Costs. IEEE/ACM Trans. Netw. 26 (6) (2018)
Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai
Contextual Bandits with Stochastic Experts. CoRR (2018)
Mikhail Kazdagli, Constantine Caramanis, Sanjay Shakkottai, Mohit Tiwari
The Shape of Alerts: Detecting Malware Using Distributed Detectors by Robustly Amplifying Transient Correlations. CoRR (2018)

Sanjay Shakkottai.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Sanjay Shakkottai