Concept

Early stopping

Related publications (47)

A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

Decentralized optimization is a powerful paradigm that finds applications in engineering and learning design. This work studies decentralized composite optimization problems with non-smooth regularization terms. Most existing gradient-based proximal decent ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2019

AdaptHD: Adaptive Efficient Training for Brain-Inspired Hyperdimensional Computing

Giovanni De Micheli, Samuel Bosch, Mohsen Imani

Brain-inspired Hyperdimensional (HD) computing is a promising solution for energy-efficient classification. However, the existing HD computing algorithms have a lack of controllability on the training iterations which often results in slow training or dive ...

2019

Patching large missing gaps of dissolved oxygen data in an intermittent stream: comparison of interpolation techniques, including machine learning models

Eco-hydrologicalmodels are useful tools for water qualitymanagement, but there implementation may require high-resolution boundary condition data which are often patchy in time due to monitoring costs. In this report, we compare the performance of gradient ...

2019

Feet Fidgeting Detection Based on Accelerometers Using Decision Tree Learning and Gradient Boosting

Kamiar Aminian

Detection of fidgeting activities is a field which has not been much explored as of now. Studies have shown that fidgeting has a beneficial impact on people’s healthiness as it burns a significant amount of energy. Being able to detect when someone is fidg ...

2018

Non-intrusive reduced order modeling of nonlinear problems using neural networks

Jan Sickmann Hesthaven, Stefano Ubbiali

We develop a non-intrusive reduced basis (RB) method for parametrized steady-state partial differential equations (PDEs). The method extracts a reduced basis from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD) and emplo ...

2018

Comparative Study on Sentence Boundary Prediction for German and English Broadcast News

Philip Neil Garner, David Imseng, Yang Wang

We present a comparative study on sentence boundary prediction for German and English broadcast news that explores generalization across different languages. In the feature extraction stage, word pause duration is firstly extracted from word aligned speech ...

Idiap2017

Adaptive regularized diffusion adaptation over multitask networks

Ali H. Sayed, Sadaf Monajemi

The focus of this paper is on multitask learning over adaptive networks where different clusters of nodes have different objectives. We propose an adaptive regularized diffusion strategy using Gaussian kernel regularization to enable the agents to learn ab ...

2015

Fast Part-Based Classification for Instrument Detection in Minimally Invasive Surgery

Pascal Fua, Raphael Sznitman, Carlos Joaquin Becker

Automatic visual detection of instruments in minimally invasive surgery (MIS) can significantly augment the procedure experience for operating clinicians. In this paper, we present a novel technique for detecting surgical instruments by constructing a robu ...

Springer2014

Learning decision rules for energy efficient building control

Colin Neil Jones

While rule based control (RBC) is current practice in most building automation systems that issue discrete control signals, recent simulation studies suggest that advanced, optimization based control methods such as hybrid model predictive control (HMPC) c ...

Elsevier2014

Adaptive Sampling for Large Scale Boosting

François Fleuret, Charles Dubout

Classical Boosting algorithms, such as AdaBoost, build a strong classifier without concern for the computational cost. Some applications, in particular in computer vision, may involve millions of training examples and very large feature spaces. In such con ...

2014

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