Siddartha Devic

According to our database, Siddartha Devic authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

When is Multicalibration Post-Processing Necessary?

Dutch Hansen, Siddartha Devic, Preetum Nakkiran, Vatsal Sharan

CoRR, 2024

Learnability is a Compact Property.

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

CoRR, 2024

Stability and Multigroup Fairness in Ranking with Uncertain Predictions.

Siddartha Devic, Aleksandra Korolova, David Kempe, Vatsal Sharan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Open Problem: Can Local Regularization Learn All Multiclass Problems?

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Regularization and Optimal Multiclass Learning.

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Fairness in Matching under Uncertainty.

Siddartha Devic, David Kempe, Vatsal Sharan, Aleksandra Korolova

Proceedings of the International Conference on Machine Learning, 2023

2022

Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions.

Zihao Deng, Siddartha Devic, Brendan Juba

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Polynomial Time Reinforcement Learning in Correlated FMDPs with Linear Value Functions.

Siddartha Devic, Zihao Deng, Brendan Juba

CoRR, 2021

Dynamic Bandwidth Allocation for PON Slicing with Performance-Guaranteed Online Convex Optimization.

Genya Ishigaki, Siddartha Devic, Riti Gour, Jason P. Jue

Proceedings of the IEEE Global Communications Conference, 2021

2020

DeepPR: Progressive Recovery for Interdependent VNFs With Deep Reinforcement Learning.

Genya Ishigaki, Siddartha Devic, Riti Gour, Jason P. Jue

IEEE J. Sel. Areas Commun., 2020

Failout: Achieving Failure-Resilient Inference in Distributed Neural Networks.

Ashkan Yousefpour, Brian Q. Nguyen, Siddartha Devic, Guanhua Wang, Aboudy Kreidieh, Hans Lobel, Alexandre M. Bayen, Jason P. Jue

CoRR, 2020

2019

Guardians of the Deep Fog: Failure-Resilient DNN Inference from Edge to Cloud.

Ashkan Yousefpour, Siddartha Devic, Brian Q. Nguyen, Aboudy Kreidieh, Alan Liao, Alexandre M. Bayen, Jason P. Jue

CoRR, 2019

DeepPR: Incremental Recovery for Interdependent VNFs with Deep Reinforcement Learning.

Genya Ishigaki, Siddartha Devic, Riti Gour, Jason P. Jue

Proceedings of the 2019 IEEE Global Communications Conference, 2019