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08/16/2022
Knowledge-Injected Federated Learning
Federated learning is an emerging technique for training models from dec...
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01/26/2022
A dual approach for federated learning
We study the federated optimization problem from a dual perspective and ...
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01/07/2022
Fair and efficient contribution valuation for vertical federated learning
Federated learning is a popular technology for training machine learning...
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09/19/2021
Improving Fairness for Data Valuation in Federated Learning
Federated learning is an emerging decentralized machine learning scheme ...
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02/12/2021
From perspective maps to epigraphical projections
The projection onto the epigraph or a level set of a closed proper conve...
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12/23/2020
NBIHT: An Efficient Algorithm for 1-bit Compressed Sensing with Optimal Error Decay Rate
The Binary Iterative Hard Thresholding (BIHT) algorithm is a popular rec...
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10/14/2020
Polar Deconvolution of Mixed Signals
The signal demixing problem seeks to separate the superposition of multi...
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06/03/2020
Online mirror descent and dual averaging: keeping pace in the dynamic case
Online mirror descent (OMD) and dual averaging (DA) are two fundamental ...
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12/11/2019
Polar Alignment and Atomic Decomposition
Structured optimization uses a prescribed set of atoms to assemble a sol...
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10/09/2019
Implementing a smooth exact penalty function for equality-constrained nonlinear optimization
We develop a general equality-constrained nonlinear optimization algorit...
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09/11/2018
Smooth Structured Prediction Using Quantum and Classical Gibbs Samplers
We introduce a quantum algorithm for solving structured-prediction probl...
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06/05/2013
Fast Dual Variational Inference for Non-Conjugate LGMs
Latent Gaussian models (LGMs) are widely used in statistics and machine ...
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04/13/2011