2 citations · 4 across the 11 of their papers we have counts for
12 papers
Welfarist Formulations for Diverse Similarity Search
Siddharth Barman, Nirjhar Das, Shivam Gupta +1
Nearest Neighbor Search (NNS) is a fundamental problem in data structures with wide-ranging applications, such as web search, recommendation systems, and, more recently, retrieval-…
Posterior Sampling by Combining Diffusion Models with Annealed Langevin Dynamics
Zhiyang Xun, Shivam Gupta, Eric Price
Given a noisy linear measurement of a distribution , and a good approximation to the prior , when can we sample from the posterior ? Posterior…
Efficient Knowledge Distillation via Curriculum Extraction
Shivam Gupta, Sushrut Karmalkar
Knowledge distillation is a technique used to train a small student network using the output generated by a large teacher network, and has many empirical advantages~\citep{Hinton20…
Entropy-Assisted Quality Pattern Identification in Finance
Rishabh Gupta, Shivam Gupta, Jaskirat Singh +1
Short-term patterns in financial time series form the cornerstone of many algorithmic trading strategies, yet extracting these patterns reliably from noisy market data remains a fo…
Faster Diffusion Sampling with Randomized Midpoints: Sequential and Parallel
Shivam Gupta, Linda Cai, Sitan Chen
Sampling algorithms play an important role in controlling the quality and runtime of diffusion model inference. In recent years, a number of works~\cite{chen2023sampling,chen2023od…
Diffusion Posterior Sampling is Computationally Intractable
Shivam Gupta, Ajil Jalal, Aditya Parulekar +2
Diffusion models are a remarkably effective way of learning and sampling from a distribution . In posterior sampling, one is also given a measurement model and…
Improved Sample Complexity Bounds for Diffusion Model Training
Shivam Gupta, Aditya Parulekar, Eric Price +1
Diffusion models have become the most popular approach to deep generative modeling of images, largely due to their empirical performance and reliability. From a theoretical standpo…
Beyond Catoni: Sharper Rates for Heavy-Tailed and Robust Mean Estimation
Shivam Gupta, Samuel B. Hopkins, Eric Price
We study the fundamental problem of estimating the mean of a -dimensional distribution with covariance given samples. When , \cite{catoni} sho…
Finite-Sample Symmetric Mean Estimation with Fisher Information Rate
Shivam Gupta, Jasper C. H. Lee, Eric Price
The mean of an unknown variance- distribution can be estimated from samples with variance and nearly corresponding subgaussian rate. When is known…
High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors
Shivam Gupta, Jasper C. H. Lee, Eric Price
In location estimation, we are given samples from a known distribution shifted by an unknown translation , and want to estimate as precisely as possible. Asymptotica…
Finite-Sample Maximum Likelihood Estimation of Location
Shivam Gupta, Jasper C. H. Lee, Eric Price +1
We consider 1-dimensional location estimation, where we estimate a parameter from samples , with each drawn i.i.d. from a known distribution . For fixed $f…
Sharp Constants in Uniformity Testing via the Huber Statistic
Shivam Gupta, Eric Price
Uniformity testing is one of the most well-studied problems in property testing, with many known test statistics, including ones based on counting collisions, singletons, and the e…