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08/01/2023
Understanding Activation Patterns in Artificial Neural Networks by Exploring Stochastic Processes
To gain a deeper understanding of the behavior and learning dynamics of ...
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07/06/2023
ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation
We present ContainerGym, a benchmark for reinforcement learning inspired...
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12/29/2022
Invariance to Quantile Selection in Distributional Continuous Control
In recent years distributional reinforcement learning has produced many ...
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07/03/2022
Recipe for Fast Large-scale SVM Training: Polishing, Parallelism, and more RAM!
Support vector machines (SVMs) are a standard method in the machine lear...
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06/21/2022
ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces
Objective: Electroencephalography (EEG) and electromyography (EMG) are t...
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01/27/2022
From Motion to Muscle
Voluntary human motion is the product of muscle activity that results fr...
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12/30/2021
Deep Transfer-Learning for patient specific model re-calibration: Application to sEMG-Classification
Accurate decoding of surface electromyography (sEMG) is pivotal for musc...
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12/01/2021
The (1+1)-ES Reliably Overcomes Saddle Points
It is known that step size adaptive evolution strategies (ES) do not con...
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11/30/2020
Improving the performance of EEG decoding using anchored-STFT in conjunction with gradient norm adversarial augmentation
Brain-computer interfaces (BCIs) enable direct communication between hum...
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11/11/2020
Non-local Optimization: Imposing Structure on Optimization Problems by Relaxation
In stochastic optimization, particularly in evolutionary computation and...
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09/20/2020
Latent Representation Prediction Networks
Deeply-learned planning methods are often based on learning representati...
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09/18/2020
Global Linear Convergence of Evolution Strategies on More Than Smooth Strongly Convex Functions
Evolution strategies (ESs) are zero-order stochastic black-box optimizat...
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09/14/2020
Methods of the Vehicle Re-identification
Most of researchers use the vehicle re-identification based on classific...
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09/14/2020
Data Augmentation and Clustering for Vehicle Make/Model Classification
Vehicle shape information is very important in Intelligent Traffic Syste...
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09/06/2020
Convergence Analysis of the Hessian Estimation Evolution Strategy
The class of algorithms called Hessian Estimation Evolution Strategies (...
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04/16/2020
Analyzing Reinforcement Learning Benchmarks with Random Weight Guessing
We propose a novel method for analyzing and visualizing the complexity o...
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03/30/2020
The Hessian Estimation Evolution Strategy
We present a novel black box optimization algorithm called Hessian Estim...
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05/15/2019
Vehicle Shape and Color Classification Using Convolutional Neural Network
This paper presents a module of vehicle reidentification based on make/m...
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10/23/2018
Challenges of Convex Quadratic Bi-objective Benchmark Problems
Convex quadratic objective functions are an important base case in state...
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06/26/2018
Dual SVM Training on a Budget
We present a dual subspace ascent algorithm for support vector machine t...
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06/26/2018
Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search
Limiting the model size of a kernel support vector machine to a pre-defi...
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06/26/2018
Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training
Budgeted Stochastic Gradient Descent (BSGD) is a state-of-the-art techni...
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06/04/2018
Challenges in High-dimensional Reinforcement Learning with Evolution Strategies
Evolution Strategies (ESs) have recently become popular for training dee...
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02/09/2018
Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success Rule
This paper explores the use of the standard approach for proving runtime...
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06/09/2017
Global Convergence of the (1+1) Evolution Strategy
We establish global convergence of the (1+1)-ES algorithm, i.e., converg...
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05/18/2017
Limited-Memory Matrix Adaptation for Large Scale Black-box Optimization
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a popula...
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04/26/2017
Limits of End-to-End Learning
End-to-end learning refers to training a possibly complex learning syste...
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05/09/2016
Anytime Bi-Objective Optimization with a Hybrid Multi-Objective CMA-ES (HMO-CMA-ES)
We propose a multi-objective optimization algorithm aimed at achieving g...
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02/10/2016
Fast model selection by limiting SVM training times
Kernelized Support Vector Machines (SVMs) are among the best performing ...
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01/15/2014
Coordinate Descent with Online Adaptation of Coordinate Frequencies
Coordinate descent (CD) algorithms have become the method of choice for ...
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05/02/2013
Testing Hypotheses by Regularized Maximum Mean Discrepancy
Do two data samples come from different distributions? Recent studies of...
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02/22/2013
Accelerated Linear SVM Training with Adaptive Variable Selection Frequencies
Support vector machine (SVM) training is an active research area since t...
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06/22/2011