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Privacy-Preserving Public Release of Datasets for Support Vector Machine Classification
We consider the problem of publicly releasing a dataset for support vect...
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Large-Scale Noun Compound Interpretation Using Bootstrapping and the Web as a Corpus
Responding to the need for semantic lexical resources in natural languag...
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Generating Semantic Adversarial Examples via Feature Manipulation
The vulnerability of deep neural networks to adversarial attacks has bee...
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Learning Coupled Policies for Simultaneous Machine Translation
In simultaneous machine translation, the system needs to incrementally g...
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Automated Discovery of Data Transformations for Robotic Process Automation
Robotic Process Automation (RPA) is a technology for automating repetiti...
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Improving Interpretability of CNN Models Using Non-Negative Concept Activation Vectors
Convolutional neural network (CNN) models for computer vision are powerf...
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OIAD: One-for-all Image Anomaly Detection with Disentanglement Learning
Anomaly detection aims to recognize samples with anomalous and unusual p...
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Clean-Label Backdoor Attacks on Video Recognition Models
Deep neural networks (DNNs) are vulnerable to backdoor attacks which can...
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Reinforcement Learning for Autonomous Defence in Software-Defined Networking
Despite the successful application of machine learning (ML) in a wide ra...
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CBHE: Corner-based Building Height Estimation for Complex Street Scene Images
Building height estimation is important in many applications such as 3D ...
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Sky pixel detection in outdoor imagery using an adaptive algorithm and machine learning
Computer vision techniques allow automated detection of sky pixels in ou...
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Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks
Recent studies have shown that DNNs can be compromised by backdoor attac...
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SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals
In response to the continuing research interest in computational semanti...
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Gaussian Process Priors for Dynamic Paired Comparison Modelling
Dynamic paired comparison models, such as Elo and Glicko, are frequently...
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Logic and the 2-Simplicial Transformer
We introduce the 2-simplicial Transformer, an extension of the Transform...
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Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness
It has been demonstrated that hidden representation learned by a deep mo...
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Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness
Evaluating the robustness of a defense model is a challenging task in ad...
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Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences
In his seminal book `The Inmates are Running the Asylum: Why High-Tech P...
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Learning how to Active Learn: A Deep Reinforcement Learning Approach
Active learning aims to select a small subset of data for annotation suc...
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Toward the Starting Line: A Systems Engineering Approach to Strong AI
Artificial General Intelligence (AGI) or Strong AI aims to create machin...
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Outcome-Oriented Predictive Process Monitoring: Review and Benchmark
Predictive business process monitoring refers to the act of making predi...
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Word Representation Models for Morphologically Rich Languages in Neural Machine Translation
Dealing with the complex word forms in morphologically rich languages is...
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Dialog state tracking, a machine reading approach using Memory Network
In an end-to-end dialog system, the aim of dialog state tracking is to a...
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Depth-Gated LSTM
In this short note, we present an extension of long short-term memory (L...
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Invariant backpropagation: how to train a transformation-invariant neural network
In many classification problems a classifier should be robust to small v...
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Towards Decoding as Continuous Optimization in Neural Machine Translation
We propose a novel decoding approach for neural machine translation (NMT...
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Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks
Despite the wide use of machine learning in adversarial settings includi...
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Unsupervised Basis Function Adaptation for Reinforcement Learning
When using reinforcement learning (RL) algorithms to evaluate a policy i...
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Geometry of Interest (GOI): Spatio-Temporal Destination Extraction and Partitioning in GPS Trajectory Data
Nowadays large amounts of GPS trajectory data is being continuously coll...
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Social planning for social HRI
Making a computational agent 'social' has implications for how it percei...
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On the Differential Privacy of Bayesian Inference
We study how to communicate findings of Bayesian inference to third part...
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Iterative Views Agreement: An Iterative Low-Rank based Structured Optimization Method to Multi-View Spectral Clustering
Multi-view spectral clustering, which aims at yielding an agreement or c...
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Unsatisfiable Cores and Lower Bounding for Constraint Programming
Constraint Programming (CP) solvers typically tackle optimization proble...
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TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs
This paper explores the suitability of using automatically discovered to...
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Ground Truth Bias in External Cluster Validity Indices
It has been noticed that some external CVIs exhibit a preferential bias ...
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Bound Founded Answer Set Programming
Answer Set Programming (ASP) is a powerful modelling formalism that is v...
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Grounding Bound Founded Answer Set Programs
To appear in Theory and Practice of Logic Programming (TPLP) Bound Fou...
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Simulation leagues: Analysis of competition formats
The selection of an appropriate competition format is critical for both ...
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On Redundant Topological Constraints
The Region Connection Calculus (RCC) is a well-known calculus for repres...
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Adjusting for Chance Clustering Comparison Measures
Adjusted for chance measures are widely used to compare partitions/clust...
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Unsatisfiable Cores for Constraint Programming
Constraint Programming (CP) solvers typically tackle optimization proble...
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Multivariate Spearman's rho for aggregating ranks using copulas
We study the problem of rank aggregation: given a set of ranked lists, w...
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Bounding Embeddings of VC Classes into Maximum Classes
One of the earliest conjectures in computational learning theory-the Sam...
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A Geometric Approach to Sample Compression
The Sample Compression Conjecture of Littlestone & Warmuth has remained ...
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A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network
We introduce a novel embedding method for knowledge base completion task...
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Analysis of Framelet Transforms on a Simplex
In this paper, we construct framelets associated with a sequence of quad...
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End-to-end Network for Twitter Geolocation Prediction and Hashing
We propose an end-to-end neural network to predict the geolocation of a ...
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A Fast and Accurate Vietnamese Word Segmenter
We propose a novel approach to Vietnamese word segmentation. Our approac...
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Paradigm Completion for Derivational Morphology
The generation of complex derived word forms has been an overlooked prob...
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Model Transfer for Tagging Low-resource Languages using a Bilingual Dictionary
Cross-lingual model transfer is a compelling and popular method for pred...
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