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Results for "Stochastic Algorithm"

KAUST Ph.D. student Jinhui Xiong wins best paper award

KAUST · Jan 20

KAUST Ph.D. student Jinhui Xiong won the best paper award at the 24th International Symposium on Vision, Modeling, and Visualization in Germany for his paper "Stochastic Convolutional Sparse Coding". The paper, co-authored with KAUST Professors Peter Richtárik and Wolfgang Heidrich, introduces a novel stochastic spatial-domain solver for Convolutional Sparse Coding (CSC). The proposed algorithm outperforms state-of-the-art solutions in terms of execution time and offers an improved representation for learning dictionaries from sample images. Why it matters: This award recognizes significant research in efficient image representation and dictionary learning, contributing to advancements in visual computing and AI at KAUST.

An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians

MBZUAI · Invalid Date

Mladen Kolar from the University of Chicago Booth School of Business discussed stochastic optimization with equality constraints at MBZUAI. He presented a stochastic algorithm based on sequential quadratic programming (SQP) using a differentiable exact augmented Lagrangian. The algorithm adapts random stepsizes using a stochastic line search procedure, establishing global "almost sure" convergence. Why it matters: The presentation highlights MBZUAI's role in hosting discussions on advanced optimization techniques, fostering research and knowledge exchange in the field of machine learning.