31 citations · 31 across the 7 of their papers we have counts for
5 papers
CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement
Mohammadreza Salehi, Mehrdad Farajtabar, Maxwell Horton +7
Contrastive language image pretraining (CLIP) is a standard method for training vision-language models. While CLIP is scalable, promptable, and robust to distribution shifts on ima…
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models
Hsuan Su, Ting-Yao Hu, Hema Swetha Koppula +5
While Automatic Speech Recognition (ASR) systems are widely used in many real-world applications, they often do not generalize well to new domains and need to be finetuned on data…
Towards Federated Learning Under Resource Constraints via Layer-wise Training and Depth Dropout
Pengfei Guo, Warren Richard Morningstar, Raviteja Vemulapalli +3
Large machine learning models trained on diverse data have recently seen unprecedented success. Federated learning enables training on private data that may otherwise be inaccessib…
Riemannian Metric Learning for Symmetric Positive Definite Matrices
Raviteja Vemulapalli, David W. Jacobs
Over the past few years, symmetric positive definite (SPD) matrices have been receiving considerable attention from computer vision community. Though various distance measures have…
MKL-RT: Multiple Kernel Learning for Ratio-trace Problems via Convex Optimization
Raviteja Vemulapalli, Vinay Praneeth Boda, Rama Chellappa
In the recent past, automatic selection or combination of kernels (or features) based on multiple kernel learning (MKL) approaches has been receiving significant attention from var…