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Found 8 papers, 0 papers with code
Linearly-involved Moreau-Enhanced-over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression
We present an efficient mathematical framework based on the linearly-involved Moreau-enhanced-over-subspace (LiMES) model.
Learning Sparse Graph with Minimax Concave Penalty under Gaussian Markov Random Fields
This paper presents a convex-analytic framework to learn sparse graphs from data.
RIJP at SemEval-2020 Task 1: Gaussian-based Embeddings for Semantic Change Detection
This paper describes the model proposed and submitted by our RIJP team to SemEval 2020 Task1: Unsupervised Lexical Semantic Change Detection.
Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces
Motivated by the success of reinforcement learning (RL) for discrete-time tasks such as AlphaGo and Atari games, there has been a recent surge of interest in using RL for continuous-time control of physical systems (cf.
Detection for 5G-NOMA: An Online Adaptive Machine Learning Approach
We propose a novel online learning based detection for the NOMA uplink.
A stochastic behavior analysis of stochastic restricted-gradient descent algorithm in reproducing kernel Hilbert spaces
This paper presents a stochastic behavior analysis of a kernel-based stochastic restricted-gradient descent method.
Adaptive Learning in Cartesian Product of Reproducing Kernel Hilbert Spaces
We propose a novel adaptive learning algorithm based on iterative orthogonal projections in the Cartesian product of multiple reproducing kernel Hilbert spaces (RKHSs).
Kernel-Based Adaptive Online Reconstruction of Coverage Maps With Side Information
In this paper, we address the problem of reconstructing coverage maps from path-loss measurements in cellular networks.
