University of Birmingham

research

∙ 01/28/2020

Margin Maximization as Lossless Maximal Compression

The ultimate goal of a supervised learning algorithm is to produce model...

Nikolaos Nikolaou, et al. ∙

research

∙ 09/23/2019

Non-monotonic Logical Reasoning Guiding Deep Learning for Explainable Visual Question Answering

State of the art algorithms for many pattern recognition problems rely o...

Heather Riley, et al. ∙

research

∙ 04/09/2019

Assessing Capsule Networks With Biased Data

Machine learning based methods achieves impressive results in object cla...

Bruno Ferrarini, et al. ∙

research

∙ 07/19/2020

Geometry Constrained Weakly Supervised Object Localization

We propose a geometry constrained network, termed GC-Net, for weakly sup...

Weizeng Lu, et al. ∙

research

∙ 01/07/2022

Repurposing Existing Deep Networks for Caption and Aesthetic-Guided Image Cropping

We propose a novel optimization framework that crops a given image based...

Nora Horanyi, et al. ∙

research

∙ 09/21/2021

Learning Interpretable Concept Groups in CNNs

We propose a novel training methodology – Concept Group Learning (CGL) –...

Saurabh Varshneya, et al. ∙

research

∙ 07/15/2019

Dynamical Systems as Temporal Feature Spaces

Parameterized state space models in the form of recurrent networks are o...

Peter Tiňo, et al. ∙

research

∙ 12/24/2021

Rediscovering Affordance: A Reinforcement Learning Perspective

Affordance refers to the perception of possible actions allowed by an ob...

Yi-Chi Liao, et al. ∙

research

∙ 01/25/2022

Combining Commonsense Reasoning and Knowledge Acquisition to Guide Deep Learning in Robotics

Algorithms based on deep network models are being used for many pattern ...

Mohan Sridharan, et al. ∙

research

∙ 07/26/2018

Level-Based Analysis of the Univariate Marginal Distribution Algorithm

Estimation of Distribution Algorithms (EDAs) are stochastic heuristics t...

Duc-Cuong Dang, et al. ∙

research

∙ 08/23/2019

Runtime Analysis of Fitness-Proportionate Selection on Linear Functions

This paper extends the runtime analysis of non-elitist evolutionary algo...

Duc-Cuong Dang, et al. ∙

research

∙ 10/11/2021

HUNTER: AI based Holistic Resource Management for Sustainable Cloud Computing

The worldwide adoption of cloud data centers (CDCs) has given rise to th...

Shreshth Tuli, et al. ∙

research

∙ 07/19/2019

VS-Net: Variable splitting network for accelerated parallel MRI reconstruction

In this work, we propose a deep learning approach for parallel magnetic ...

Jinming Duan, et al. ∙

research

∙ 04/24/2013

Comparison of several reweighted l1-algorithms for solving cardinality minimization problems

Reweighted l1-algorithms have attracted a lot of attention in the field ...

Mohammad Javad Abdi, et al. ∙

research

∙ 03/24/2020

G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features

In this paper, we propose a novel real-time 6D object pose estimation fr...

Wei Chen, et al. ∙

research

∙ 07/10/2020

SeqHAND:RGB-Sequence-Based 3D Hand Pose and Shape Estimation

3D hand pose estimation based on RGB images has been studied for a long ...

John Yang, et al. ∙

research

∙ 11/30/2017

Spatially-Adaptive Filter Units for Deep Neural Networks

Classical deep convolutional networks increase receptive field size by e...

Domen Tabernik, et al. ∙

research

∙ 07/10/2017

Understanding State Preferences With Text As Data: Introducing the UN General Debate Corpus

Every year at the United Nations, member states deliver statements durin...

Alexander Baturo, et al. ∙

research

∙ 05/15/2017

Kernel Truncated Regression Representation for Robust Subspace Clustering

Subspace clustering aims to group data points into multiple clusters of ...

Liangli Zhen, et al. ∙

research

∙ 04/20/2015

Negatively Correlated Search

Evolutionary Algorithms (EAs) have been shown to be powerful tools for c...

Ke Tang, et al. ∙

research

∙ 03/24/2017

Rejection-free Ensemble MCMC with applications to Factorial Hidden Markov Models

Bayesian inference for complex models is challenging due to the need to ...

Kaspar Märtens, et al. ∙

research

∙ 03/22/2017

Testing and Learning on Distributions with Symmetric Noise Invariance

Kernel embeddings of distributions and the Maximum Mean Discrepancy (MMD...

Ho Chung Leon Law, et al. ∙

research

∙ 03/13/2017

Probabilistic Matching: Causal Inference under Measurement Errors

The abundance of data produced daily from large variety of sources has b...

Fani Tsapeli, et al. ∙

research

∙ 08/14/2013

Average Drift Analysis and Population Scalability

This paper aims to study how the population size affects the computation...

Jun He, et al. ∙

research

∙ 04/08/2013

Synaptic Scaling Balances Learning in a Spiking Model of Neocortex

Learning in the brain requires complementary mechanisms: potentiation an...

Mark Rowan, et al. ∙

research

∙ 02/20/2017

Bayesian Boolean Matrix Factorisation

Boolean matrix factorisation aims to decompose a binary data matrix into...

Tammo Rukat, et al. ∙

research

∙ 03/28/2012

On the Easiest and Hardest Fitness Functions

The hardness of fitness functions is an important research topic in the ...

Jun He, et al. ∙

research

∙ 11/09/2011

Scaling Up Estimation of Distribution Algorithms For Continuous Optimization

Since Estimation of Distribution Algorithms (EDA) were proposed, many at...

Weishan Dong, et al. ∙

research

∙ 06/30/2011

Effects of Compensation, Connectivity and Tau in a Computational Model of Alzheimer's Disease

This work updates an existing, simplistic computational model of Alzheim...

Mark Rowan, et al. ∙

research

∙ 12/14/2010

On the Impact of Mutation-Selection Balance on the Runtime of Evolutionary Algorithms

The interplay between mutation and selection plays a fundamental role in...

Per Kristian Lehre, et al. ∙

research

∙ 03/11/2016

High-dimensional Black-box Optimization via Divide and Approximate Conquer

Divide and Conquer (DC) is conceptually well suited to high-dimensional ...

Peng Yang, et al. ∙

research

∙ 03/12/2017

Detection of Human Rights Violations in Images: Can Convolutional Neural Networks help?

After setting the performance benchmarks for image, video, speech and au...

Grigorios Kalliatakis, et al. ∙

research

∙ 03/12/2017

Evaluating Deep Convolutional Neural Networks for Material Classification

Determining the material category of a surface from an image is a demand...

Grigorios Kalliatakis, et al. ∙

research

∙ 08/17/2015

A Refinement-Based Architecture for Knowledge Representation and Reasoning in Robotics

This paper describes an architecture that combines the complementary str...

Mohan Sridharan, et al. ∙

research

∙ 11/19/2016

Semantic tracking: Single-target tracking with inter-supervised convolutional networks

This article presents a semantic tracker which simultaneously tracks a s...

Jingjing Xiao, et al. ∙

research

∙ 05/05/2014

KR^3: An Architecture for Knowledge Representation and Reasoning in Robotics

This paper describes an architecture that combines the complementary str...

Shiqi Zhang, et al. ∙

research

∙ 02/23/2014

Discriminative Functional Connectivity Measures for Brain Decoding

We propose a statistical learning model for classifying cognitive proces...

Orhan Firat, et al. ∙

research

∙ 09/15/2016

Visual Stability Prediction and Its Application to Manipulation

Understanding physical phenomena is a key competence that enables humans...

Wenbin Li, et al. ∙

research

∙ 09/13/2016

Towards Deep Compositional Networks

Hierarchical feature learning based on convolutional neural networks (CN...

Domen Tabernik, et al. ∙

research

∙ 05/19/2016

Automatic Selection of the Optimal Local Feature Detector

A large number of different feature detectors has been proposed so far. ...

Bruno Ferrarini, et al. ∙

research

∙ 10/20/2011

A Version of Geiringer-like Theorem for Decision Making in the Environments with Randomness and Incomplete Information

Purpose: In recent years Monte-Carlo sampling methods, such as Monte Car...

Boris Mitavskiy, et al. ∙

research

∙ 03/04/2015

A Hierarchical Approach for Joint Multi-view Object Pose Estimation and Categorization

We propose a joint object pose estimation and categorization approach wh...

M. Ozay, et al. ∙

research

∙ 02/20/2015

Visual object tracking performance measures revisited

The problem of visual tracking evaluation is sporting a large variety of...

Luka Čehovin, et al. ∙

research

∙ 02/17/2015

Semi-supervised Segmentation Fusion of Multi-spectral and Aerial Images

A Semi-supervised Segmentation Fusion algorithm is proposed using consen...

M. Ozay, et al. ∙

research

∙ 08/29/2017

A Simple LSTM model for Transition-based Dependency Parsing

We present a simple LSTM-based transition-based dependency parser. Our m...

Mohab Elkaref, et al. ∙

research

∙ 08/19/2017

What Drives the International Development Agenda? An NLP Analysis of the United Nations General Debate 1970-2016

There is surprisingly little known about agenda setting for internationa...

Alexander Baturo, et al. ∙

research

∙ 07/18/2016

Dependency Language Models for Transition-based Dependency Parsing

In this paper, we present an approach to improve the accuracy of a stron...

Juntao Yu, et al. ∙

research

∙ 12/12/2017

Grasp that optimises objectives along post-grasp trajectories

In this article, we study the problem of selecting a grasping pose on th...

Amir M Ghalamzan E, et al. ∙

research

∙ 11/10/2017

A Theoretical Analysis of Sparse Recovery Stability of Dantzig Selector and LASSO

Dantzig selector (DS) and LASSO problems have attracted plenty of attent...

Yun-Bin Zhao, et al. ∙

research

∙ 08/07/2017

On the Learnability of Programming Language Semantics

Game semantics is a powerful method of semantic analysis for programming...

Dan R. Ghica, et al. ∙

University of Birmingham

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