Search Results for author: Georgios C. Anagnostopoulos

Found 9 papers, 3 papers with code

Multi-Task Learning with Group-Specific Feature Space Sharing

1 code implementation13 Aug 2015 Niloofar Yousefi, Michael Georgiopoulos, Georgios C. Anagnostopoulos

When faced with learning a set of inter-related tasks from a limited amount of usable data, learning each task independently may lead to poor generalization performance.

Binary Classification Multi-Task Learning

Conic Multi-Task Classification

1 code implementation20 Aug 2014 Cong Li, Michael Georgiopoulos, Georgios C. Anagnostopoulos

Traditionally, Multi-task Learning (MTL) models optimize the average of task-related objective functions, which is an intuitive approach and which we will be referring to as Average MTL.

Classification General Classification +1

Hash Function Learning via Codewords

1 code implementation13 Aug 2015 Yinjie Huang, Michael Georgiopoulos, Georgios C. Anagnostopoulos

In this paper we introduce a novel hash learning framework that has two main distinguishing features, when compared to past approaches.

Content-Based Image Retrieval Retrieval

Pareto-Path Multi-Task Multiple Kernel Learning

no code implementations11 Apr 2014 Cong Li, Michael Georgiopoulos, Georgios C. Anagnostopoulos

A traditional and intuitively appealing Multi-Task Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing amongst tasks.

Multi-Task Learning

A Unifying Framework for Typical Multi-Task Multiple Kernel Learning Problems

no code implementations21 Jan 2014 Cong Li, Michael Georgiopoulos, Georgios C. Anagnostopoulos

Over the past few years, Multi-Kernel Learning (MKL) has received significant attention among data-driven feature selection techniques in the context of kernel-based learning.

feature selection Multi-Task Learning

Multi-Task Classification Hypothesis Space with Improved Generalization Bounds

no code implementations9 Dec 2013 Cong Li, Michael Georgiopoulos, Georgios C. Anagnostopoulos

This paper presents a RKHS, in general, of vector-valued functions intended to be used as hypothesis space for multi-task classification.

Classification General Classification +2

Learning Hash Function through Codewords

no code implementations22 Feb 2019 Yinjie Huang, Michael Georgiopoulos, Georgios C. Anagnostopoulos

In this paper, we propose a novel hash learning approach that has the following main distinguishing features, when compared to past frameworks.

Content-Based Image Retrieval Retrieval

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