Pinned Repositories
Accelerated-Coordinate-Descent-Method
The implementation of Coordinate Descent Method Accelerated by Universal Metaalgorithm with efficient amortised complexity of iteration & Experiments with sparse SoftMax function, where the proposed method is better than FGM
Cayley-non-flat-embeddings
Let’s train various models to embed Cayley graphs to hyperbolic plane and then study, how much can we say about groups from these embeddings. At the same time, let’s study models generalization ability, by changing their hyperparameters.
highlight
HighLight – platform for teamworking on translations of medical documents
Lambda-algebra-tools
Neural-homotopy-groups-calculation
Sampling-from-homotopy-groups-of-spheres
Sampling from π_n(S^2). Application of optimization and machine learning methods to problems of algebraic topology
Sirius-2021-DPD-optimization
Experiments on stochastic optimization for digital pre-distortion of the signal
torch-alternating
This module provides the extension for PyTorch toolkit, containing imlplementations of some alternating optimization methods acting as envelopes for arbitrary optimizers applied to the problem considered.
Wasserstein-distance-calculation
Optimal Transport and Optimization related experiments.
OPTAMI
This package is dedicated to high-order optimization methods. All the methods can be used similarly to standard PyTorch optimizers.
dmivilensky's Repositories
dmivilensky/Wasserstein-distance-calculation
Optimal Transport and Optimization related experiments.
dmivilensky/Sampling-from-homotopy-groups-of-spheres
Sampling from π_n(S^2). Application of optimization and machine learning methods to problems of algebraic topology
dmivilensky/Sirius-2021-DPD-optimization
Experiments on stochastic optimization for digital pre-distortion of the signal
dmivilensky/highlight
HighLight – platform for teamworking on translations of medical documents
dmivilensky/Cayley-non-flat-embeddings
Let’s train various models to embed Cayley graphs to hyperbolic plane and then study, how much can we say about groups from these embeddings. At the same time, let’s study models generalization ability, by changing their hyperparameters.
dmivilensky/Neural-homotopy-groups-calculation
dmivilensky/torch-alternating
This module provides the extension for PyTorch toolkit, containing imlplementations of some alternating optimization methods acting as envelopes for arbitrary optimizers applied to the problem considered.
dmivilensky/Accelerated-Coordinate-Descent-Method
The implementation of Coordinate Descent Method Accelerated by Universal Metaalgorithm with efficient amortised complexity of iteration & Experiments with sparse SoftMax function, where the proposed method is better than FGM
dmivilensky/Adaptive-relatively-smooth-optimization
We introduce the new concept of (α,L,δ)-relative smoothness (see https://arxiv.org/pdf/2107.05765.pdf) which covers both the concept of relative smoothness and relative Lipschitz continuity. For the corresponding class of problems, we propose some adaptive and universal methods which have optimal estimates of the convergence rate.
dmivilensky/Canonical-barriers
Numerical solution of Painlevé III D7 equation and calculation of canonical barriers according to arXiv:1806.06588
dmivilensky/Lambda-algebra-tools
dmivilensky/compilers-course-jb
dmivilensky/Goidle
dmivilensky/Network-utility-maximization-2021
dmivilensky/Sliding-for-Kernel-SVM
We consider a problem of minimizing a sum of two functions and propose a generic algorithmic framework (SAE) to separate oracle complexities for each function. We compare the performance of splitting accelerated enveloped accelerated variance reduced method with a different sliding technique.
dmivilensky/Solar-method-non-convex-optimisation
dmivilensky/Typology-of-caritive
This repo is a part of a typological study of caritive — a cluster of meanings describing the absence of an object at the disposal of some participant of the situation. We study the statistical properties of expert measurements of caritive indicators to find a dependencies between them