52 citations · 143 across the 11 of their papers we have counts for
11 papers
Efficient Exploration at Scale
Seyed Mohammad Asghari, Chris Chute, Vikranth Dwaracherla +5
We develop an online learning algorithm that dramatically improves the data efficiency of reinforcement learning from human feedback (RLHF). Our algorithm incrementally updates rew…
Computational Scaling in Inverse Photonic Design Through Factorization Caching
Ahmet Onur Dasdemir, Victor Minden, Emir Salih Magden
Inverse design coupled with adjoint optimization is a powerful method to design on-chip nanophotonic devices with multi-wavelength and multi-mode optical functionalities. Although…
Synthetic DOmain-Targeted Augmentation (S-DOTA) Improves Model Generalization in Digital Pathology
Sai Chowdary Gullapally, Yibo Zhang, Nitin Kumar Mittal +20
Machine learning algorithms have the potential to improve patient outcomes in digital pathology. However, generalization of these tools is currently limited by sensitivity to varia…
Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics
Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii
Artificial neural networks that learn to perform Principal Component Analysis (PCA) and related tasks using strictly local learning rules have been previously derived based on the…
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching
Andrea Giovannucci, Victor Minden, Cengiz Pehlevan +1
Big data problems frequently require processing datasets in a streaming fashion, either because all data are available at once but collectively are larger than available memory or…
A simple solver for the fractional Laplacian in multiple dimensions
Victor Minden, Lexing Ying
We present a simple discretization scheme for the hypersingular integral representation of the fractional Laplace operator and solver for the corresponding fractional Laplacian pro…