Abstract: The Potts model is defined on all possible colourings of vertices in q>1 possible values (q=2 corresponds to the Ising model). The distribution depends on the external parameter T>0 ...
1 Department of Computer Science, University of California, Irvine, Irvine, CA, United States 2 Department of Electrical Engineering & Computer Science, United States Military Academy, West Point, NY, ...
Abstract: In this paper, a smoothing neural network (SNN) is proposed for a class of constrained non-Lipschitz optimization problems, where the objective function is the sum of a nonsmooth, nonconvex ...
Training large-scale transformers stably has been a longstanding challenge in deep learning, particularly as models grow in size and expressivity. MIT researchers tackle a persistent problem at its ...
Abstract: In many practical learning problems, training samples are not i.i.d., and there is an intrinsic dependency among samples. Therefore, theoretical study of learning with dependent data has ...
This repository contains the research paper and code related to Uniform Convergence of Lipschitz Functions with Dependent Gaussian Samples. The work provides theoretical bounds for learning Lipschitz ...
TORONTO, Dec. 04, 2024 (GLOBE NEWSWIRE) -- Firefly Neuroscience, Inc. (“Firefly,” “we,” or the “Company”) (NASDAQ: AIFF), an Artificial Intelligence ...
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