3 citations · 3 across the 2 of their papers we have counts for
8 papers · 1 filter
Loss Barcode: A Topological Measure of Escapability in Loss Landscapes
Serguei Barannikov, Daria Voronkova, Alexander Mironenko +4
Neural network training is commonly based on SGD. However, the understanding of SGD's ability to converge to good local minima, given the non-convex nature of loss functions and th…
Uncovering Challenges of Solving the Continuous Gromov-Wasserstein Problem
Xavier Aramayo Carrasco, Maksim Nekrashevich, Petr Mokrov +2
Recently, the Gromov-Wasserstein Optimal Transport (GWOT) problem has attracted the special attention of the ML community. In this problem, given two distributions supported on two…
Light Unbalanced Optimal Transport
Milena Gazdieva, Arip Asadulaev, Alexander Korotin +1
While the continuous Entropic Optimal Transport (EOT) field has been actively developing in recent years, it became evident that the classic EOT problem is prone to different issue…
Barcodes as Summary of Loss Function Topology
Serguei Barannikov, Alexander Korotin, Dmitry Oganesyan +2
We propose to study neural networks' loss surfaces by methods of topological data analysis. We suggest to apply barcodes of Morse complexes to explore topology of loss surfaces. An…
Online Algorithm for Aggregating Experts' Predictions with Unbounded Quadratic Loss
Alexander Korotin, Vladimir V'yugin, Evgeny Burnaev
We consider the problem of online aggregation of expert predictions with the quadratic loss function. We propose an algorithm for aggregating expert predictions which does not requ…
Mixability of Integral Losses: a Key to Efficient Online Aggregation of Functional and Probabilistic Forecasts
Alexander Korotin, Vladimir V'yugin, Evgeny Burnaev
In this paper we extend the setting of the online prediction with expert advice to function-valued forecasts. At each step of the online game several experts predict a function, an…