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Margin Maximization as Lossless Maximal Compression
The ultimate goal of a supervised learning algorithm is to produce model...
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Better Boosting with Bandits for Online Learning
Probability estimates generated by boosting ensembles are poorly calibra...
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A Deep Neural Network for Finger Counting and Numerosity Estimation
In this paper, we present neuro-robotics models with a deep artificial n...
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Multi-Temporal High Resolution Aerial Image Registration Using Semantic Features
A new type of segmentation-based semantic feature (SegSF) for multi-temp...
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ATIS + SpiNNaker: a Fully Event-based Visual Tracking Demonstration
The Asynchronous Time-based Image Sensor (ATIS) and the Spiking Neural N...
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Multi-Label Zero-Shot Human Action Recognition via Joint Latent Embedding
Human action recognition refers to automatic recognizing human actions f...
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Meta-QSAR: a large-scale application of meta-learning to drug design and discovery
We investigate the learning of quantitative structure activity relations...
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Visualisation of Survey Responses using Self-Organising Maps: A Case Study on Diabetes Self-care Factors
Due to the chronic nature of diabetes, patient self-care factors play an...
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Dependency Injection for Programming by Optimization
Programming by Optimization tools perform automatic software configurati...
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Identifying networks with common organizational principles
Many complex systems can be represented as networks, and the problem of ...
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Alternative Semantic Representations for Zero-Shot Human Action Recognition
A proper semantic representation for encoding side information is key to...
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Monotonicity of Fitness Landscapes and Mutation Rate Control
The typical view in evolutionary biology is that mutation rates are mini...
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Deploying learning materials to game content for serious education game development: A case study
The ultimate goals of serious education games (SEG) are to facilitate le...
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An associative memory for the on-line recognition and prediction of temporal sequences
This paper presents the design of an associative memory with feedback th...
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GPflow: A Gaussian process library using TensorFlow
GPflow is a Gaussian process library that uses TensorFlow for its core c...
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Novelty Detection on a Mobile Robot Using Habituation
In this paper a novelty filter is introduced which allows a robot operat...
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A Real-Time Novelty Detector for a Mobile Robot
Recognising new or unusual features of an environment is an ability whic...
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Novelty Detection for Robot Neotaxis
The ability of a robot to detect and respond to changes in its environme...
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Learning Constructive Primitives for Online Level Generation and Real-time Content Adaptation in Super Mario Bros
Procedural content generation (PCG) is of great interest to game design ...
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Temporal ordering of clinical events
This report describes a minimalistic set of methods engineered to anchor...
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Algorithm for Adapting Cases Represented in a Tractable Description Logic
Case-based reasoning (CBR) based on description logics (DLs) has gained ...
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Zero-Shot Visual Recognition via Bidirectional Latent Embedding
Zero-shot learning for visual recognition, e.g., object and action recog...
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Syntactic vs. Semantic Locality: How Good Is a Cheap Approximation?
Extracting a subset of a given OWL ontology that captures all the ontolo...
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Principal Autoparallel Analysis: Data Analysis in Weitzenböck Space
The statistical analysis of data lying on a differentiable, locally Eucl...
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Reasoning with Very Expressive Fuzzy Description Logics
It is widely recognized today that the management of imprecision and vag...
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Variational Gaussian Process Dynamical Systems
High dimensional time series are endemic in applications of machine lear...
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Direct high-order edge-preserving regularization for tomographic image reconstruction
In this paper we present a new two-level iterative algorithm for tomogra...
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Robust Face Recognition with Structural Binary Gradient Patterns
This paper presents a computationally efficient yet powerful binary fram...
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Multi-agent learning using Fictitious Play and Extended Kalman Filter
Decentralised optimisation tasks are important components of multi-agent...
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A Note on the Complexity of the Satisfiability Problem for Graded Modal Logics
Graded modal logic is the formal language obtained from ordinary (propos...
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Bayesian Mixture Models for Frequent Itemset Discovery
In binary-transaction data-mining, traditional frequent itemset mining o...
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Adaptive Forgetting Factor Fictitious Play
It is now well known that decentralised optimisation can be formulated a...
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Reasoning with Individuals for the Description Logic SHIQ
While there has been a great deal of work on the development of reasonin...
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Practical Reasoning for Expressive Description Logics
Description Logics (DLs) are a family of knowledge representation formal...
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Practical Reasoning for Very Expressive Description Logics
Description Logics (DLs) are a family of knowledge representation formal...
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Reasoning with Axioms: Theory and Pratice
When reasoning in description, modal or temporal logics it is often usef...
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Variational Inducing Kernels for Sparse Convolved Multiple Output Gaussian Processes
Interest in multioutput kernel methods is increasing, whether under the ...
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Sparse Convolved Multiple Output Gaussian Processes
Recently there has been an increasing interest in methods that deal with...
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How big is big enough? Unsupervised word sense disambiguation using a very large corpus
In this paper, the problem of disambiguating a target word for Polish is...
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Investigating how well contextual features are captured by bi-directional recurrent neural network models
Learning algorithms for natural language processing (NLP) tasks traditio...
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A computational investigation of sources of variability in sentence comprehension difficulty in aphasia
We present a computational evaluation of three hypotheses about sources ...
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As Cool as a Cucumber: Towards a Corpus of Contemporary Similes in Serbian
Similes are natural language expressions used to compare unlikely things...
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Complexity and universality in the long-range order of words
As is the case of many signals produced by complex systems, language pre...
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What do we need to build explainable AI systems for the medical domain?
Artificial intelligence (AI) generally and machine learning (ML) specifi...
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A Story of Parametric Trace Slicing, Garbage and Static Analysis
This paper presents a proposal (story) of how statically detecting unrea...
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Etymo: A New Discovery Engine for AI Research
We present Etymo (https://etymo.io), a discovery engine to facilitate ar...
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Probabilistic Canonical Correlation Analysis: A Whitening Approach
Canonical correlation analysis (CCA) is a classic and widely used statis...
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The K-Nearest Neighbour UCB algorithm for multi-armed bandits with covariates
In this paper we propose and explore the k-Nearest Neighbour UCB algorit...
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On the Performance of Network NOMA in Uplink CoMP Systems: A Stochastic Geometry Approach
To improve the system throughput, this paper proposes a network non-orth...
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Fine-Grained Energy Profiling for Deep Convolutional Neural Networks on the Jetson TX1
Energy-use is a key concern when migrating current deep learning applica...
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