
TopDown Networks: A coarsetofine reimagination of CNNs
Biological vision adopts a coarsetofine information processing pathway...
read it

Symbolic Regression Methods for Reinforcement Learning
Reinforcement learning algorithms can be used to optimally solve dynamic...
read it

Maximizing Information Gain in Partially Observable Environments via Prediction Reward
Information gathering in a partially observable environment can be formu...
read it

EdgeNets:Edge Varying Graph Neural Networks
Driven by the outstanding performance of neural networks in the structur...
read it

Matrix Product Operator Restricted Boltzmann Machines
A restricted Boltzmann machine (RBM) learns a probability distribution o...
read it

TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise
Robustness to label noise is a critical property for weaklysupervised c...
read it

Finegrained Classification of Rowing teams
Finegrained classification tasks such as identifying different breeds o...
read it

Enhancing Robustness of Online Learning Models on Highly Noisy Data
Classification algorithms have been widely adopted to detect anomalies f...
read it

Probabilistic Recursive Reasoning for MultiAgent Reinforcement Learning
Humans are capable of attributing latent mental contents such as beliefs...
read it

Visionbased Navigation Using Deep Reinforcement Learning
Deep reinforcement learning (RL) has been successfully applied to a vari...
read it

How do neural networks see depth in single images?
Deep neural networks have lead to a breakthrough in depth estimation fro...
read it

Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning
With the increasing number of data collectors such as smartphones, immen...
read it

Consistency and Finite Sample Behavior of Binary Class Probability Estimation
In this work we investigate to which extent one can recover class probab...
read it

A Sufficient Statistic for Influence in Structured Multiagent Environments
Making decisions in complex environments is a key challenge in artificia...
read it

UneVEn: Universal Value Exploration for MultiAgent Reinforcement Learning
This paper focuses on cooperative valuebased multiagent reinforcement ...
read it

Helping users discover perspectives: Enhancing opinion mining with joint topic models
Support or opposition concerning a debated claim such as abortion should...
read it

Testing with Fewer Resources: An Adaptive Approach to PerformanceAware Test Case Generation
Automated test case generation is an effective technique to yield highc...
read it

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning
This paper introduces MDP homomorphic networks for deep reinforcement le...
read it

Anomaly Detection in a Digital Video Broadcasting System Using Timed Automata
This paper focuses on detecting anomalies in a digital video broadcastin...
read it

Efficient exploration with Double Uncertain Value Networks
This paper studies directed exploration for reinforcement learning agent...
read it

Attended Endtoend Architecture for Age Estimation from Facial Expression Videos
The main challenges of age estimation from facial expression videos lie ...
read it

Complexity of Scheduling Charging in the Smart Grid
In the smart grid, the intent is to use flexibility in demand, both to b...
read it

Regularization via Mass Transportation
The goal of regression and classification methods in supervised learning...
read it

Supervised Classification: Quite a Brief Overview
The original problem of supervised classification considers the task of ...
read it

On reducing sampling variance in covariate shift using control variates
Covariate shift classification problems can in principle be tackled by i...
read it

MR AcquisitionInvariant Representation Learning
Voxelwise classification is a popular and effective method for tissue qu...
read it

Accelerating CS in Parallel Imaging Reconstructions Using an Efficient and Effective Circulant Preconditioner
Purpose: Design of a preconditioner for fast and efficient parallel imag...
read it

Responsible Autonomy
As intelligent systems are increasingly making decisions that directly a...
read it

Emotion in Reinforcement Learning Agents and Robots: A Survey
This article provides the first survey of computational models of emotio...
read it

On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL
In various approaches to learning, notably in domain adaptation, active ...
read it

Target contrastive pessimistic risk for robust domain adaptation
In domain adaptation, classifiers with information from a source domain ...
read it

Nuclear Discrepancy for Active Learning
Active learning algorithms propose which unlabeled objects should be que...
read it

Multiple Instance Learning: A Survey of Problem Characteristics and Applications
Multiple instance learning (MIL) is a form of weakly supervised learning...
read it

Learning Multimodal Transition Dynamics for ModelBased Reinforcement Learning
In this paper we study how to learn stochastic, multimodal transition dy...
read it

ScaleRegularized Filter Learning
We start out by demonstrating that an elementary learning task, correspo...
read it

Interpreting Finite Automata for Sequential Data
Automaton models are often seen as interpretable models. Interpretabilit...
read it

Active Learning Using Uncertainty Information
Many active learning methods belong to the retrainingbased approaches, ...
read it

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

The Pessimistic Limits of Marginbased Losses in Semisupervised Learning
We show that for linear classifiers defined by convex marginbased surro...
read it

Solving the L1 regularized least square problem via a boxconstrained smooth minimization
In this paper, an equivalent smooth minimization for the L1 regularized ...
read it

Optimistic Semisupervised Least Squares Classification
The goal of semisupervised learning is to improve supervised classifier...
read it

Fast kNN mode seeking clustering applied to active learning
A significantly faster algorithm is presented for the original kNN mode ...
read it

InfluenceOptimistic Local Values for Multiagent Planning  Extended Version
Recent years have seen the development of methods for multiagent plannin...
read it

Temporal AttentionGated Model for Robust Sequence Classification
Typical techniques for sequence classification are designed for wellseg...
read it

A sequential Monte Carlo approach to Thompson sampling for Bayesian optimization
Bayesian optimization through Gaussian process regression is an effectiv...
read it

Online Optimization with Costly and Noisy Measurements using Random Fourier Expansions
This paper analyzes DONE, an online optimization algorithm that iterativ...
read it

Projected Estimators for Robust Semisupervised Classification
For semisupervised techniques to be applied safely in practice we at le...
read it

System Identification through Online Sparse Gaussian Process Regression with Input Noise
There has been a growing interest in using nonparametric regression met...
read it

Robust Semisupervised Least Squares Classification by Implicit Constraints
We introduce the implicitly constrained least squares (ICLS) classifier,...
read it

FeatureLevel Domain Adaptation
Domain adaptation is the supervised learning setting in which the traini...
read it
Delft University of Technology
Delft University of Technology also known as TU Delft, is the largest and oldest Dutch public technological university, located in Delft, Netherlands.