منابع مشابه
Stochastic, Distributed and Federated Optimization for Machine Learning
We study optimization algorithms for the finite sum problems frequently arising in machine learning applications. First, we propose novel variants of stochastic gradient descent with a variance reduction property that enables linear convergence for strongly convex objectives. Second, we study distributed setting, in which the data describing the optimization problem does not fit into a single c...
متن کاملStochastic Search with Locally Clustered Targets: Learning from T Cells
Searching a space with locally clustered targets (think picking apples from trees) leads to an optimization problem: When should the searcher leave the current region, and invest the time to travel to another one? We consider here a model of such a search process: infection screening by T cells in the immune system. Taking an AIS perspective, we ask whether this model could provide insight for ...
متن کاملStochastic clustered-dot dithering
A new technique for building stochastic clustered-dot screens is being proposed. A large dither matrix comprising thousands of stochastically laid out screen dots is constructed by first laying out the screen dot centers. Screen dot centers are obtained by placing discrete disks of a chosen radius at free cell locations when traversing the dither array cells according to either a discretely rot...
متن کاملFederated Multi-Task Learning
Federated learning poses new statistical and systems challenges in training machinelearning models over distributed networks of devices. In this work, we show thatmulti-task learning is naturally suited to handle the statistical challenges of thissetting, and propose a novel systems-aware optimization method, MOCHA, that isrobust to practical systems issues. Our method and theor...
متن کاملEntity Resolution and Federated Learning get a Federated Resolution
Consider two data providers, each maintaining records of different feature sets about common entities. They aim to learn a linear model over the whole set of features. This problem of federated learning over vertically partitioned data includes a crucial upstream issue: entity resolution, i.e. finding the correspondence between the rows of the datasets. It is well known that entity resolution, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Social Science Research Network
سال: 2023
ISSN: ['1556-5068']
DOI: https://doi.org/10.2139/ssrn.4331052