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04/01/2023
An active-set based recursive approach for solving convex isotonic regression with generalized order restrictions
This paper studies the convex isotonic regression with generalized order...
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02/16/2022
Data-Driven Minimax Optimization with Expectation Constraints
Attention to data-driven optimization approaches, including the well-kno...
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12/28/2021
Robust Security Analysis Based on Random Geometry Theory for Satellite-Terrestrial-Vehicle Network
Driven by B5G and 6G technologies, multi-network fusion is an indispensa...
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10/23/2021
On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization
In this paper, we propose a general procedure for establishing the lands...
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08/03/2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization
In this paper, we consider the geometric landscape connection of the wid...
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11/17/2020
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence
In this paper, we propose a new ecursive mportance ketching algorithm fo...
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11/06/2020
A dynamic programming approach for generalized nearly isotonic optimization
Shape restricted statistical estimation problems have been extensively s...
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10/07/2020
Design of Power-Imbalanced SCMA Codebook
Sparse code multiple access (SCMA) is a promising multiuser communicatio...
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05/07/2020
Noisy Differentiable Architecture Search
Simplicity is the ultimate sophistication. Differentiable Architecture S...
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02/27/2020
Exploration-efficient Deep Reinforcement Learning with Demonstration Guidance for Robot Control
Although deep reinforcement learning (DRL) algorithms have made importan...
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02/19/2020
Neural Architecture Search For Fault Diagnosis
Data-driven methods have made great progress in fault diagnosis, especia...
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01/16/2020
MixPath: A Unified Approach for One-shot Neural Architecture Search
The expressiveness of search space is a key concern in neural architectu...
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06/28/2019
Learning Markov models via low-rank optimization
Modeling unknown systems from data is a precursor of system optimization...
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04/03/2018
Estimation of Markov Chain via Rank-constrained Likelihood
This paper studies the recovery and state compression of low-rank Markov...
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12/11/2017