76 citations · 357 across the 44 of their papers we have counts for
11 papers · 1 filter
Conditional Flow Matching for Transport Between Markov Processes
Syamantak Kumar, Dheeraj Nagaraj, Saptarshi Roy +1
Motivated by sequence-to-sequence transport in the context time-series domain adaptation, we study the problem of transportation between trajectories of Markov processes. Given a l…
Walk fast but be careful: Understanding Parallel Sampling in Masked Diffusion
Vansh Bansal, Cho Cholyeon, Cholyeon Cho +3
In this paper, we use random walks on graphs as a verifiable sandbox for studying parallel sampling strategies in masked diffusion models (MDMs). We train an MDM on random walk sam…
On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA
Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar +1
We study high-dimensional differentially private (DP) covariance estimation in the operator norm, and principal component analysis (PCA), under -row-column sparsity (-RCS) of…
Low-Precision Streaming PCA
Sanjoy Dasgupta, Syamantak Kumar, Shourya Pandey +1
Low-precision streaming PCA estimates the top principal component in a streaming setting under limited precision. We establish an information-theoretic lower bound on the quantizat…
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion
Akhil Jalan, Yassir Jedra, Arya Mazumdar +2
We study transfer learning for matrix completion in a Missing Not-at-Random (MNAR) setting that is motivated by biological problems. The target matrix has entire rows and colum…
Dimension-free Score Matching and Time Bootstrapping for Diffusion Models
Syamantak Kumar, Dheeraj Nagaraj, Purnamrita Sarkar
Diffusion models generate samples by estimating the score function of the target distribution at various noise levels. The model is trained using samples drawn from the target dist…