47 citations · 87 across the 6 of their papers we have counts for
8 papers
A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs
Ankit Singh Rawat, Veeranjaneyulu Sadhanala, Afshin Rostamizadeh +12
A primary challenge in large language model (LLM) development is their onerous pre-training cost. Typically, such pre-training involves optimizing a self-supervised objective (such…
EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval
Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer +6
Large neural models (such as Transformers) achieve state-of-the-art performance for information retrieval (IR). In this paper, we aim to improve distillation methods that pave the…
Exponential Family Trend Filtering on Lattices
Veeranjaneyulu Sadhanala, Robert Bassett, James Sharpnack +1
Trend filtering is a modern approach to nonparametric regression that is more adaptive to local smoothness than splines or similar basis procedures. Existing analyses of trend filt…
Multivariate Trend Filtering for Lattice Data
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Addison J. Hu +1
We study a multivariate version of trend filtering, called Kronecker trend filtering or KTF, for the case in which the design points form a lattice in dimensions. KTF is a natu…
A Higher-Order Kolmogorov-Smirnov Test
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Aaditya Ramdas +1
We present an extension of the Kolmogorov-Smirnov (KS) two-sample test, which can be more sensitive to differences in the tails. Our test statistic is an integral probability metri…
Additive Models with Trend Filtering
Veeranjaneyulu Sadhanala, Ryan J. Tibshirani
We study additive models built with trend filtering, i.e., additive models whose components are each regularized by the (discrete) total variation of their th (discrete) derivat…
Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Ryan Tibshirani
We consider the problem of estimating a function defined over locations on a -dimensional grid (having all side lengths equal to ). When the function is constrained…
Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms
Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai +3
We develop parallel and distributed Frank-Wolfe algorithms; the former on shared memory machines with mini-batching, and the latter in a delayed update framework. Whenever possible…