ProfessorsProfessors of University of AlbertaNidhi Hegde

Nidhi Hegde

University of Alberta

H-index: 22

North America-Canada

About Nidhi Hegde

Nidhi Hegde, With an exceptional h-index of 22 and a recent h-index of 9 (since 2020), a distinguished researcher at University of Alberta, specializes in the field of Privacy, Fairness and Bias, Resource allocation, Online Learning, Reinforcement Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning

System and method for machine learning architecture with privacy-preserving node embeddings

Long Term Fairness via Performative Distributionally Robust Optimization

Near-optimal thompson sampling-based algorithms for differentially private stochastic bandits

Long Term Fairness for Minority Groups via Performative Distributionally Robust Optimization

Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum

Multi type mean field reinforcement learning

System and method for multi-type mean field reinforcement machine learning

Nidhi Hegde Information

University	University of Alberta
Position	___
Citations(all)	1509
Citations(since 2020)	409
Cited By	1274
hIndex(all)	22
hIndex(since 2020)	9
i10Index(all)	32
i10Index(since 2020)	9
Email	Access Email
University Profile Page	University of Alberta
Google Scholar	View Google Scholar Profile

Nidhi Hegde Skills & Research Interests

Privacy

Fairness and Bias

Resource allocation

Online Learning

Reinforcement Learning

Top articles of Nidhi Hegde

Title	Journal	Author(s)	Publication Date
Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning		Bingshan Hu Tianyue H Zhang Nidhi Hegde Mark Schmidt	2023/7/2
System and method for machine learning architecture with privacy-preserving node embeddings			2020/11/26
Long Term Fairness via Performative Distributionally Robust Optimization		Garnet Liam Peet-Pare Nidhi Hegde Alona Fyshe	2022/9/29
Near-optimal thompson sampling-based algorithms for differentially private stochastic bandits		Bingshan Hu Nidhi Hegde	2022/8/17
Long Term Fairness for Minority Groups via Performative Distributionally Robust Optimization	arXiv preprint arXiv:2207.05777	Liam Peet-Pare Nidhi Hegde Alona Fyshe	2022/7/12
Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum		Kirby Banman Garnet Liam Peet-Pare Nidhi Hegde Alona Fyshe Martha White	2021/9/29
Multi type mean field reinforcement learning		Sriram Ganapathi Subramanian Pascal Poupart Matthew E Taylor Nidhi Hegde	2020/5
System and method for multi-type mean field reinforcement machine learning			2020/9/3