Advertisement

Topics

Accelerating Sequential Minimal Optimization via Stochastic Subgradient Descent.

07:00 EST 5th February 2019 | BioPortfolio

Summary of "Accelerating Sequential Minimal Optimization via Stochastic Subgradient Descent."

Sequential minimal optimization (SMO) is one of the most popular methods for solving a variety of support vector machines (SVMs). The shrinking and caching techniques are commonly used to accelerate SMO. An interesting phenomenon of SMO is that most of the computational time is wasted on the first half of iterations for building a good solution closing to the optimal. However, as we all know, the stochastic subgradient descent (SSGD) method is extremely fast for building a good solution. In this paper, we propose a generalized framework of accelerating SMO through SSGD for a variety of SVMs of binary classification, regression, ordinal regression, and so on. We also provide a deep insight about why SSGD can accelerate SMO. Experimental results on a variety of datasets and learning applications confirm that our method can effectively speed up SMO.

Affiliation

Journal Details

This article was published in the following journal.

Name: IEEE transactions on cybernetics
ISSN: 2168-2275
Pages:

Links

DeepDyve research library

PubMed Articles [4872 Associated PubMed Articles listed on BioPortfolio]

Dualityfree Methods for Stochastic Composition Optimization.

In this paper, we consider the composition optimization with two expected-value functions in the form of (1/n)Σni = 1 Fi((1/m)Σmj = 1 Gj(x))+R(x), which formulates many important problems in statist...

Research on a learning rate with energy index in deep learning.

The stochastic gradient descent algorithm (SGD) is the main optimization solution in deep learning. The performance of SGD depends critically on how learning rates are tuned over time. In this paper, ...

A stochastic variational framework for Recurrent Gaussian Processes models.

Gaussian Processes (GPs) models have been successfully applied to the problem of learning from sequential observations. In such context, the family of Recurrent Gaussian Processes (RGPs) have been rec...

An Accelerated Linearly Convergent Stochastic L-BFGS Algorithm.

The limited memory version of the Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm is the most popular quasi-Newton algorithm in machine learning and optimization. Recently, it was shown that the s...

Giant cell arteritis in patients of Indian Subcontinental descent in the UK.

GCA in the Indian Subcontinent (ISC) is rare. Our centre in London, UK, serves an ethnically diverse population, including a significant population of patients of ISC descent. We hypothesise that pati...

Clinical Trials [2171 Associated Clinical Trials listed on BioPortfolio]

Stochastic Resonance Stimulation in Brain Plasticity and Post Stroke Motor Recovery

This study evaluates the effectiveness of stochastic resonance electric stimulation on neuromuscular control and proprioception in healthy and individuals with stroke.

Non Invasive Vestibular Stimulation in Modulation of Vestibular and Balance Function

Background: Patients with bilateral vestibular hypofunction (BVH) frequently presented with dysequilibrium, dizziness and oscillopsia, leading to increased risk for fall. The mainstream fo...

Efficacy and Outcomes of a Non-Pharmacological Intervention for Neonatal Abstinence Syndrome

The purpose of this study is to examine the efficacy of a specially-constructed crib mattress that delivers gentle vibrations (stochastic vibrotactile stimulation) as a complementary, non-...

Sequential Optimization of Dose and Schedule of PfSPZ Vaccine

MAVACHE is a sequential dose and schedule optimization trial of intravenous immunization with PfSPZ Vaccine in 18 to 54 malaria-naïve, healthy adult volunteers receiving 9x10^5, 1.35x10^6...

FREEDOM - A Frequent Optimization Study Using the QuickOpt Method

The objective of this study is to demonstrate that frequent atrio-ventricular (AV/PV) and inter-ventricular (V-V) delay optimization using QuickOpt in patients with CRT-D device results in...

Medical and Biotech [MESH] Definitions

Devices for accelerating protons or electrons in closed orbits where the accelerating voltage and magnetic field strength varies (the accelerating voltage is held constant for electrons) in order to keep the orbit radius constant.

Processes that incorporate some element of randomness, used particularly to refer to a time series of random variables.

A type of oropharyngeal airway that provides an alternative to endotracheal intubation and standard mask anesthesia in certain patients. It is introduced into the hypopharynx to form a seal around the larynx thus permitting spontaneous or positive pressure ventilation without penetration of the larynx or esophagus. It is used in place of a facemask in routine anesthesia. The advantages over standard mask anesthesia are better airway control, minimal anesthetic gas leakage, a secure airway during patient transport to the recovery area, and minimal postoperative problems.

A stochastic process such that the conditional probability distribution for a state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system.

Abscission-accelerating plant growth substance isolated from young cotton fruit, leaves of sycamore, birch, and other plants, and from potatoes, lemons, avocados, and other fruits.

Advertisement
Quick Search
Advertisement
Advertisement

 


DeepDyve research library

Searches Linking to this Article