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03/02/2023
Improved Space Bounds for Learning with Experts
We give improved tradeoffs between space and regret for the online learn...
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02/28/2023
High Probability Convergence of Stochastic Gradient Methods
In this work, we describe a generic approach to show convergence with hi...
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10/31/2022
Improved Learning-augmented Algorithms for k-means and k-medians Clustering
We consider the problem of clustering in the learning-augmented setting,...
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10/25/2022
Streaming Submodular Maximization with Differential Privacy
In this work, we study the problem of privately maximizing a submodular ...
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09/23/2022
An Efficient Algorithm for Fair Multi-Agent Multi-Armed Bandit with Low Regret
Recently a multi-agent variant of the classical multi-armed bandit was p...
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07/22/2022
Fair Range k-center
We study the problem of fairness in k-centers clustering on data with di...
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04/20/2022
Improved Worst-Group Robustness via Classifier Retraining on Independent Splits
High-capacity deep neural networks (DNNs) trained with Empirical Risk Mi...
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03/01/2022
Private Frequency Estimation via Projective Geometry
In this work, we propose a new algorithm ProjectiveGeometryResponse (PGR...
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03/10/2021
Linear Constraints Learning for Spiking Neurons
Encoding information with precise spike timings using spike-coded neuron...
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02/15/2021
Fair and Optimal Cohort Selection for Linear Utilities
The rise of algorithmic decision-making has created an explosion of rese...
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12/14/2020
Constraints on Hebbian and STDP learned weights of a spiking neuron
We analyse mathematically the constraints on weights resulting from Hebb...
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08/27/2020