
ADAPT : Awesome Domain Adaptation Python Toolbox
ADAPT is an opensource python library providing the implementation of s...
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Concentration Inequalities for TwoSample Rank Processes with Application to Bipartite Ranking
The ROC curve is the gold standard for measuring the performance of a te...
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DiscrepancyBased Active Learning for Domain Adaptation
The goal of the paper is to design active learning strategies which lead...
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Robust Kernel Density Estimation with MedianofMeans principle
In this paper, we introduce a robust nonparametric density estimator com...
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Offline detection of changepoints in the mean for stationary graph signals
This paper addresses the problem of segmenting a stream of graph signals...
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Adversarial Weighting for Domain Adaptation in Regression
We present a novel instance based approach to handle regression tasks in...
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Dynamic Epidemic Control via Sequential Resource Allocation
In the Dynamic Resource Allocation (DRA) problem, an administrator has t...
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Optimal Multiple Stopping Rule for WarmStarting Sequential Selection
In this paper we present the Warmstarting Dynamic Thresholding algorith...
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Detecting multiple changepoints in the timevarying Ising model
This work focuses on the estimation of changepoints in a timevarying I...
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Sequential Dynamic Resource Allocation for Epidemic Control
Under the Dynamic Resource Allocation (DRA) model, an administrator has ...
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Multivariate Convolutional Sparse Coding with Low Rank Tensor
This paper introduces a new multivariate convolutional sparse coding bas...
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Revealing posturographic features associated with the risk of falling in patients with Parkinsonian syndromes via machine learning
Falling in Parkinsonian syndromes (PS) is associated with postural insta...
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The MultiRound Sequential Selection Problem
In the Sequential Selection Problem (SSP), immediate and irrevocable dec...
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ruptures: change point detection in Python
ruptures is a Python library for offline change point detection. This pa...
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A review of change point detection methods
In this work, methods to detect one or several change points in multivar...
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A Spectral Method for Activity Shaping in ContinuousTime Information Cascades
Information Cascades Model captures dynamical properties of user activit...
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Distributed Convolutional Sparse Coding
We consider the problem of building shiftinvariant representations for ...
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Global optimization of Lipschitz functions
The goal of the paper is to design sequential strategies which lead to e...
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A ranking approach to global optimization
We consider the problem of maximizing an unknown function over a compact...
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Stochastic Process Bandits: Upper Confidence Bounds Algorithms via Generic Chaining
The paper considers the problem of global optimization in the setup of s...
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Optimization for Gaussian Processes via Chaining
In this paper, we consider the problem of stochastic optimization under ...
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Gaussian Process Optimization with Mutual Information
In this paper, we analyze a generic algorithm scheme for sequential glob...
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Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration
In this paper, we consider the challenge of maximizing an unknown functi...
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Link Prediction in Graphs with Autoregressive Features
In the paper, we consider the problem of link prediction in timeevolvin...
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Estimation of Simultaneously Sparse and Low Rank Matrices
The paper introduces a penalized matrix estimation procedure aiming at s...
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Graph Prediction in a LowRank and Autoregressive Setting
We study the problem of prediction for evolving graph data. We formulate...
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A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs
We consider the two problems of predicting links in a dynamic graph sequ...
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