Search Results for author:
Found 4 papers, 1 papers with code
RETSim: Resilient and Efficient Text Similarity
This paper introduces RETSim (Resilient and Efficient Text Similarity), a lightweight, multilingual deep learning model trained to produce robust metric embeddings for near-duplicate text retrieval, clustering, and dataset deduplication tasks.
Transformers in Healthcare: A Survey
With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications.
A Novel Convergence Analysis for the Stochastic Proximal Point Algorithm
In this paper, we study the stochastic proximal point algorithm (SPPA) for general empirical risk minimization (ERM) problems as well as deep learning problems.
Stochastic Proximal Point Algorithm for Large-scale Nonconvex Optimization: Convergence, Implementation, and Application to Neural Networks
SPPA has been shown to converge faster and more stable than the celebrated stochastic gradient descent (SGD) algorithm, and its many variations, for convex problems.
