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Found 6 papers, 3 papers with code
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm
Their communication, governed by the communication topology and gossip weight matrices, facilitates the exchange of model updates.
Subsampling Error in Stochastic Gradient Langevin Diffusions
Indeed, we introduce and study the Stochastic Gradient Langevin Diffusion (SGLDiff), a continuous-time Markov process that follows the Langevin diffusion corresponding to a data subset and switches this data subset after exponential waiting times.
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
In particular, when the adaptation target is a series of domains, the adaptation accuracy of AdaNPC is 50% higher than advanced TTA methods.
Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate
In the proposed family, EquiStatic has a degree of $\Theta(\ln(n))$, where $n$ is the network size, and a series of time-dependent one-peer topologies, EquiDyn, has a constant degree of 1.
Losing momentum in continuous-time stochastic optimisation
This model is a piecewise-deterministic Markov process that represents the particle movement by an underdamped dynamical system and the data subsampling through a stochastic switching of the dynamical system.
A Continuous-time Stochastic Gradient Descent Method for Continuous Data
Optimization problems with continuous data appear in, e. g., robust machine learning, functional data analysis, and variational inference.
