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07/07/2023
Fermat Distances: Metric Approximation, Spectral Convergence, and Clustering Algorithms
We analyze the convergence properties of Fermat distances, a family of d...
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05/30/2023
It begins with a boundary: A geometric view on probabilistically robust learning
Although deep neural networks have achieved super-human performance on m...
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01/31/2023
Faster Predict-and-Optimize with Three-Operator Splitting
In many practical settings, a combinatorial problem must be repeatedly s...
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06/02/2021
Learn to Predict Equilibria via Fixed Point Networks
Systems of interacting agents can often be modeled as contextual games, ...
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03/23/2021
Fixed Point Networks: Implicit Depth Models with Jacobian-Free Backprop
A growing trend in deep learning replaces fixed depth models by approxim...
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02/21/2021
A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization
We consider the zeroth-order optimization problem in the huge-scale sett...
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12/17/2020
Balancing Geometry and Density: Path Distances on High-Dimensional Data
New geometric and computational analyses of power-weighted shortest-path...
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11/24/2020
Who killed Lilly Kane? A case study in applying knowledge graphs to crime fiction
We present a preliminary study of a knowledge graph created from season ...
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10/06/2020
SCOBO: Sparsity-Aware Comparison Oracle Based Optimization
We study derivative-free optimization for convex functions where we furt...
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03/29/2020
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling
We consider the problem of minimizing a high-dimensional objective funct...
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05/30/2019
Power Weighted Shortest Paths for Unsupervised Learning
We study the use of power weighted shortest path distance functions for ...
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08/17/2018
Semi-Supervised Cluster Extraction via a Compressive Sensing Approach
We use techniques from compressive sensing to design a local clustering ...
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08/30/2017