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01/17/2023
Optimal Algorithms for Latent Bandits with Cluster Structure
We consider the problem of latent bandits with cluster structure where t...
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10/29/2022
Improved Support Recovery in Universal One-bit Compressed Sensing
One-bit compressed sensing (1bCS) is an extremely quantized signal acqui...
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10/07/2022
Private and Efficient Meta-Learning with Low Rank and Sparse Decomposition
Meta-learning is critical for a variety of practical ML systems – like p...
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09/08/2022
Online Low Rank Matrix Completion
We study the problem of online low-rank matrix completion with 𝖬 users, ...
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06/22/2022
Community Recovery in the Geometric Block Model
To capture inherent geometric features of many community detection probl...
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05/26/2022
On Learning Mixture of Linear Regressions in the Non-Realizable Setting
While mixture of linear regressions (MLR) is a well-studied topic, prior...
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02/24/2022
On Learning Mixture Models with Sparse Parameters
Mixture models are widely used to fit complex and multimodal datasets. I...
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10/02/2021
Random Subgraph Detection Using Queries
The planted densest subgraph detection problem refers to the task of tes...
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09/02/2021
Lower Bounds on the Total Variation Distance Between Mixtures of Two Gaussians
Mixtures of high dimensional Gaussian distributions have been studied ex...
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07/19/2021
Support Recovery in Universal One-bit Compressed Sensing
One-bit compressed sensing (1bCS) is an extreme-quantized signal acquisi...
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06/10/2021
Support Recovery of Sparse Signals from a Mixture of Linear Measurements
Recovery of support of a sparse vector from simple measurements is a wid...
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06/04/2021
Fuzzy Clustering with Similarity Queries
The fuzzy or soft k-means objective is a popular generalization of the w...
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01/29/2021
Learning User Preferences in Non-Stationary Environments
Recommendation systems often use online collaborative filtering (CF) alg...
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10/22/2020
Recovery of sparse linear classifiers from mixture of responses
In the problem of learning a mixture of linear classifiers, the aim is t...
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06/29/2020
Recovery of Sparse Signals from a Mixture of Linear Samples
Mixture of linear regressions is a popular learning theoretic model that...
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01/19/2020
Algebraic and Analytic Approaches for Parameter Learning in Mixture Models
We present two different approaches for parameter learning in several mi...
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10/30/2019
Sample Complexity of Learning Mixtures of Sparse Linear Regressions
In the problem of learning mixtures of linear regressions, the goal is t...
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10/28/2019
Same-Cluster Querying for Overlapping Clusters
Overlapping clusters are common in models of many practical data-segment...
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04/21/2019
Trace Reconstruction: Generalized and Parameterized
In the beautifully simple-to-state problem of trace reconstruction, the ...
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03/31/2019
Semisupervised Clustering by Queries and Locally Encodable Source Coding
Source coding is the canonical problem of data compression in informatio...
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06/29/2018
High Dimensional Discrete Integration by Hashing and Optimization
Recently Ermon et al. (2013) pioneered an ingenuous way to practically c...
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04/12/2018
Connectivity in Random Annulus Graphs and the Geometric Block Model
Random geometric graphs are the simplest, and perhaps the earliest possi...
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09/16/2017