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Distributed Optimization

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The goal of Distributed Optimization is to optimize a certain objective defined over millions of billions of data that is distributed over many machines by utilizing the computational power of these machines.

Source: Analysis of Distributed StochasticDual Coordinate Ascent

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/leepei/dplbfgs

공식 코드

A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization

https://github.com/liboyue/Network-Distributed-Algorithm

공식 코드

Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction

https://github.com/limaries30/distributed-td-learning

공식 코드

A primal-dual perspective for distributed TD-learning

https://github.com/litian96/FedDANE

공식 코드

FedDANE: A Federated Newton-Type Method

https://github.com/litian96/FedProx

공식 코드

Federated Optimization in Heterogeneous Networks

https://github.com/lsu-raise-lab/dplib

공식 코드

DPLib: A Standard Benchmark Library for Distributed Power System Analysis and Optimization

https://github.com/mmkamani7/LUPA-SGD

공식 코드

Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization

https://github.com/nandofioretto/GpuBE

공식 코드

Accelerating Exact and Approximate Inference for (Distributed) Discrete Optimization with GPUs

https://github.com/nikitinvv/tomoalign

공식 코드

Distributed optimization for nonrigid nano-tomography

https://github.com/nikolausdemmel/rootba

공식 코드

Power Bundle Adjustment for Large-Scale 3D Reconstruction

https://github.com/nikosimus/br-lsvrg

공식 코드

Byzantine-Robust Loopless Stochastic Variance-Reduced Gradient

https://github.com/nikosimus/cc-for-br-learning

공식 코드

Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates

https://github.com/optml/CoCoA

공식 코드

Distributed Optimization with Arbitrary Local Solvers

https://github.com/papachristoumarios/dp-distributed-estimation

공식 코드

Differentially Private Distributed Estimation and Learning

https://github.com/polixir/zoopt

공식 코드

ZOOpt: Toolbox for Derivative-Free Optimization

https://github.com/qiongxiu/PrivacyOptimizationSubspace

공식 코드

Privacy-Preserving Distributed Optimization via Subspace Perturbation: A General Framework

https://github.com/qqqyang/shuffle-qudio

공식 코드

Shuffle-QUDIO: accelerate distributed VQE with trainability enhancement and measurement reduction

https://github.com/rajarshisaha95/distoptconstrcomm

공식 코드

Efficient Randomized Subspace Embeddings for Distributed Optimization under a Communication Budget

https://github.com/s-huu/pmtl

공식 코드

Private Multi-Task Learning: Formulation and Applications to Federated Learning

https://github.com/sambuddhac/horizontal_proper

공식 코드

Transmission Investment Coordination using MILP Lagrange Dual Decomposition and Auxiliary Problem Principle

https://github.com/schemmy/CoCoA-Experiments

공식 코드

An Accelerated Communication-Efficient Primal-Dual Optimization Framework for Structured Machine Learning

https://github.com/shams-sam/fedoptim

공식 코드

Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?

https://github.com/sholly-offis/Deta

공식 코드

Dynamic communication topologies for distributed heuristics in energy system optimization algorithms

https://github.com/shubhamjha-46/wz_estimators

공식 코드

Wyner-Ziv Estimators for Distributed Mean Estimation with Side Information and Optimization

https://github.com/simonwebertum/poba

공식 코드

Power Bundle Adjustment for Large-Scale 3D Reconstruction

https://github.com/sisl/distributed_admm_sampler

공식 코드

Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers

https://github.com/sourajitdas/State-Augmented-Routing-Wireless-Communication

공식 코드

Opportunistic Routing in Wireless Communications via Learnable State-Augmented Policies

https://github.com/um-iral/resource-aware-coordination-airsim

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Communication- and Computation-Efficient Distributed Submodular Optimization in Robot Mesh Networks

https://github.com/unic-lab/qedgix

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GNN-Empowered Effective Partial Observation MARL Method for AoI Management in Multi-UAV Network

https://github.com/vineeths96/Gradient-Compression

공식 코드

Unbiased Single-scale and Multi-scale Quantizers for Distributed Optimization

https://github.com/vineeths96/heterogeneous-systems

공식 코드

Distributed Optimization using Heterogeneous Compute Systems

https://github.com/vishnupandi/FedNDL3

공식 코드

On the Convergence of Decentralized Federated Learning Under Imperfect Information Sharing

https://github.com/vvipgupta/OverSketchedNewton

공식 코드

OverSketched Newton: Fast Convex Optimization for Serverless Systems

https://github.com/xuchen0427/fairsync

공식 코드

FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval

https://github.com/yandex-research/btard

공식 코드

Secure Distributed Training at Scale

https://github.com/yandex-research/moshpit-sgd

공식 코드

Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.