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06/03/2019
Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement
Satellite-based positioning system such as GPS often suffers from large ...
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01/30/2019
Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee
Factorization machine (FM) is a popular machine learning model to captur...
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12/05/2018
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series
Decomposing complex time series into trend, seasonality, and remainder c...
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07/17/2018
Parallel Restarted SGD for Non-Convex Optimization with Faster Convergence and Less Communication
For large scale non-convex stochastic optimization, parallel mini-batch ...
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05/25/2018
Large-scale Distance Metric Learning with Uncertainty
Distance metric learning (DML) has been studied extensively in the past ...
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05/21/2018
Learning with Non-Convex Truncated Losses by SGD
Learning with a convex loss function has been a dominating paradigm for...
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05/19/2018
Robust Optimization over Multiple Domains
Recently, machine learning becomes important for the cloud computing ser...
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05/08/2018
Multinomial Logit Bandit with Linear Utility Functions
Multinomial logit bandit is a sequential subset selection problem which ...
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01/24/2018
PRNN: Recurrent Neural Network with Persistent Memory
Although Recurrent Neural Network (RNN) has been a powerful tool for mod...
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07/24/2017
Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM
Although deep learning models are highly effective for various learning ...
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05/04/2015
An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection
In this paper, we consider the problem of column subset selection. We pr...
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04/15/2015
Theory of Dual-sparse Regularized Randomized Reduction
In this paper, we study randomized reduction methods, which reduce high-...
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03/22/2014
CUR Algorithm with Incomplete Matrix Observation
CUR matrix decomposition is a randomized algorithm that can efficiently ...
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02/03/2014
Fine-Grained Visual Categorization via Multi-stage Metric Learning
Fine-grained visual categorization (FGVC) is to categorize objects into ...
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05/09/2013
Stochastic gradient descent algorithms for strongly convex functions at O(1/T) convergence rates
With a weighting scheme proportional to t, a traditional stochastic grad...
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12/25/2012
Large Scale Strongly Supervised Ensemble Metric Learning, with Applications to Face Verification and Retrieval
Learning Mahanalobis distance metrics in a high- dimensional feature spa...
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05/09/2012