
Surrogatefree machine learningbased organ dose reconstruction for pediatric abdominal radiotherapy
To study radiotherapyrelated adverse effects, detailed dose information...
read it

A Biologically Plausible Learning Rule for Deep Learning in the Brain
Researchers have proposed that deep learning, which is providing importa...
read it

Robust temporal difference learning for critical domains
We present a new Qfunction operator for temporal difference (TD) learni...
read it

Effective and Efficient Computation with Multipletimescale Spiking Recurrent Neural Networks
The emergence of braininspired neuromorphic computing as a paradigm for...
read it

Observer variationaware medical image segmentation by combining deep learning and surrogateassisted genetic algorithms
There has recently been great progress in automatic segmentation of medi...
read it

Machine learning for automatic construction of pseudorealistic pediatric abdominal phantoms
Machine Learning (ML) is proving extremely beneficial in many healthcare...
read it

A ConeBeam XRay CT Data Collection Designed for Machine Learning
Unlike previous works, this open data collection consists of Xray cone...
read it

Prediction Scores as a Window into Classifier Behavior
Most multiclass classifiers make their prediction for a test sample by ...
read it

A Tight Excess Risk Bound via a Unified PACBayesianRademacherShtarkovMDL Complexity
We present a novel notion of complexity that interpolates between and ge...
read it

Identification of Probabilities
Within psychology, neuroscience and artificial intelligence, there has b...
read it

Common Knowledge in a Logic of Gossips
Gossip protocols aim at arriving, by means of pointtopoint or group co...
read it

Lenient MultiAgent Deep Reinforcement Learning
A significant amount of research in recent years has been dedicated towa...
read it

Efficient forward propagation of timesequences in convolutional neural networks using Deep Shifting
When a Convolutional Neural Network is used for onthefly evaluation of...
read it

Conditional Time Series Forecasting with Convolutional Neural Networks
We present a method for conditional time series forecasting based on the...
read it

Can we reach Pareto optimal outcomes using bottomup approaches?
Traditionally, researchers in decision making have focused on attempting...
read it

Technical Report: Towards a Universal Code Formatter through Machine Learning
There are many declarative frameworks that allow us to implement code fo...
read it

Translucent Players: Explaining Cooperative Behavior in Social Dilemmas
In the last few decades, numerous experiments have shown that humans do ...
read it

Epistemic Protocols for Distributed Gossiping
Gossip protocols aim at arriving, by means of pointtopoint or group co...
read it

Fractionally Predictive Spiking Neurons
Recent experimental work has suggested that the neural firing rate can b...
read it

A Discipline of Evolutionary Programming
Genetic fitness optimization using small populations or small population...
read it

CompAdaGrad: A Compressed, Complementary, ComputationallyEfficient Adaptive Gradient Method
The adaptive gradient online learning method known as AdaGrad has seen w...
read it

Fast Rates for General Unbounded Loss Functions: from ERM to Generalized Bayes
We present new excess risk bounds for general unbounded loss functions i...
read it

Online Isotonic Regression
We consider the online version of the isotonic regression problem. Given...
read it

Maximin Action Identification: A New Bandit Framework for Games
We study an original problem of pure exploration in a strategic bandit m...
read it

Timed Soft Concurrent Constraint Programs: An Interleaved and a Parallel Approach
We propose a timed and soft extension of Concurrent Constraint Programmi...
read it

Fast rates in statistical and online learning
The speed with which a learning algorithm converges as it is presented w...
read it

Estimating the Maximum Expected Value: An Analysis of (Nested) Cross Validation and the Maximum Sample Average
We investigate the accuracy of the two most common estimators for the ma...
read it

A method for locally approximating regularized iterative tomographic reconstruction methods
In many applications of tomography, the acquired projections are either ...
read it

Solving Weighted Voting Game Design Problems Optimally: Representations, Synthesis, and Enumeration
We study the inverse power index problem for weighted voting games: the ...
read it

HorizonIndependent Optimal Prediction with LogLoss in Exponential Families
We study online learning under logarithmic loss with regular parametric ...
read it

Follow the Leader If You Can, Hedge If You Must
FollowtheLeader (FTL) is an intuitive sequential prediction strategy t...
read it

Web Similarity
Normalized web distance (NWD) is a similarity or normalized semantic dis...
read it

Exact Expression For Information Distance
Information distance can be defined not only between two strings but als...
read it

Adaptive Hedge
Most methods for decisiontheoretic online learning are based on the Hed...
read it

Generic identification of binaryvalued hidden Markov processes
The generic identification problem is to decide whether a stochastic pro...
read it

Applying MDL to Learning Best Model Granularity
The Minimum Description Length (MDL) principle is solidly based on a pro...
read it

Constraint Programming viewed as Rulebased Programming
We study here a natural situation when constraint programming can be ent...
read it

Automatic Generation of Constraint Propagation Algorithms for Small Finite Domains
We study here constraint satisfaction problems that are based on predefi...
read it

The Rough Guide to Constraint Propagation
We provide here a simple, yet very general framework that allows us to e...
read it

An Algebraic Programming Style for Numerical Software and its Optimization
The abstract mathematical theory of partial differential equations (PDEs...
read it

Minimum Description Length Induction, Bayesianism, and Kolmogorov Complexity
The relationship between the Bayesian approach and the minimum descripti...
read it

Catching Up Faster by Switching Sooner: A Prequential Solution to the AICBIC Dilemma
Bayesian model averaging, model selection and its approximations such as...
read it

Normalized Compression Distance of Multisets with Applications
Normalized compression distance (NCD) is a parameterfree, featurefree,...
read it

Information Distance: New Developments
In pattern recognition, learning, and data mining one obtains informatio...
read it

Normalized Information Distance is Not Semicomputable
Normalized information distance (NID) uses the theoretical notion of Kol...
read it

Information Distance in Multiples
Information distance is a parameterfree similarity measure based on com...
read it

A New Quartet Tree Heuristic for Hierarchical Clustering
We consider the problem of constructing an an optimalweight tree from t...
read it

Similarity of Objects and the Meaning of Words
We survey the emerging area of compressionbased, parameterfree, simila...
read it

Clustering by compression
We present a new method for clustering based on compression. The method ...
read it

The similarity metric
A new class of distances appropriate for measuring similarity relations ...
read it
Centrum Wiskunde & Informatica
The Centrum Wiskunde & Informatica is a research center in the field of mathematics and theoretical computer science.