Chalmers University of Technology

research

∙ 07/29/2021

Contemporary Symbolic Regression Methods and their Relative Performance

Many promising approaches to symbolic regression have been presented in ...

William La Cava, et al. ∙

research

∙ 03/02/2020

Differential Privacy at Risk: Bridging Randomness and Privacy Budget

The calibration of noise for a privacy-preserving mechanism depends on t...

Ashish Dandekar, et al. ∙

research

∙ 11/15/2019

Automated Augmentation with Reinforcement Learning and GANs for Robust Identification of Traffic Signs using Front Camera Images

Traffic sign identification using camera images from vehicles plays a cr...

Sohini Roy Chowdhury, et al. ∙

research

∙ 05/12/2019

NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding

Research on depth-based human activity analysis achieved outstanding per...

Jun Liu, et al. ∙

research

∙ 05/13/2020

Pose Proposal Critic: Robust Pose Refinement by Learning Reprojection Errors

In recent years, considerable progress has been made for the task of rig...

Lucas Brynte, et al. ∙

research

∙ 03/05/2021

Unsupervised Learning for Robust Fitting:A Reinforcement Learning Approach

Robust model fitting is a core algorithm in a large number of computer v...

Giang Truong, et al. ∙

research

∙ 04/21/2020

ParkPredict: Motion and Intent Prediction of Vehicles in Parking Lots

We investigate the problem of predicting driver behavior in parking lots...

Xu Shen, et al. ∙

research

∙ 11/03/2021

Online Learning of Energy Consumption for Navigation of Electric Vehicles

Energy-efficient navigation constitutes an important challenge in electr...

Niklas Åkerblom, et al. ∙

research

∙ 01/25/2020

Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

We propose a model-based machine-learning approach for polarization-mult...

Christian Häger, et al. ∙

research

∙ 03/03/2020

An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles

Energy-efficient navigation constitutes an important challenge in electr...

Niklas Åkerblom, et al. ∙

research

∙ 06/13/2022

Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africa

Observational studies of causal effects require adjustment for confoundi...

Connor T. Jerzak, et al. ∙

research

∙ 06/22/2022

Sharing pattern submodels for prediction with missing values

Missing values are unavoidable in many applications of machine learning ...

Lena Stempfle, et al. ∙

research

∙ 09/06/2021

Thompson Sampling for Bandits with Clustered Arms

We propose algorithms based on a multi-level Thompson sampling scheme, f...

Emil Carlsson, et al. ∙

research

∙ 09/21/2018

LIDAR-Camera Fusion for Road Detection Using Fully Convolutional Neural Networks

In this work, a deep learning approach has been developed to carry out r...

Luca Caltagirone, et al. ∙

research

∙ 02/08/2019

Skeleton-Based Online Action Prediction Using Scale Selection Network

Action prediction is to recognize the class label of an ongoing activity...

Jun Liu, et al. ∙

research

∙ 03/23/2020

Learning End-to-End Codes for the BPSK-constrained Gaussian Wiretap Channel

Finite-length codes are learned for the Gaussian wiretap channel in an e...

Alireza Nooraiepour, et al. ∙

research

∙ 03/04/2019

Incremental Visual-Inertial 3D Mesh Generation with Structural Regularities

Visual-Inertial Odometry (VIO) algorithms typically rely on a point clou...

Antoni Rosinol, et al. ∙

research

∙ 11/28/2019

Lidar-Camera Co-Training for Semi-Supervised Road Detection

Recent advances in the field of machine learning and computer vision hav...

Luca Caltagirone, et al. ∙

research

∙ 01/15/2019

Feature Boosting Network For 3D Pose Estimation

In this paper, a feature boosting network is proposed for estimating 3D ...

Jun Liu, et al. ∙

research

∙ 08/01/2019

Learning When to Drive in Intersections by Combining Reinforcement Learning and Model Predictive Control

In this paper, we propose a decision making algorithm intended for autom...

Tommy Tram, et al. ∙

research

∙ 05/07/2020

Lifted Regression/Reconstruction Networks

In this work we propose lifted regression/reconstruction networks (LRRNs...

Rasmus Kjær Høier, et al. ∙

research

∙ 05/11/2020

Reference Pose Generation for Visual Localization via Learned Features and View Synthesis

Visual Localization is one of the key enabling technologies for autonomo...

Zichao Zhang, et al. ∙

research

∙ 10/17/2017

Nonlinear Interference Mitigation via Deep Neural Networks

A neural-network-based approach is presented to efficiently implement di...

Christian Häger, et al. ∙

research

∙ 05/09/2017

Paving the Roadway for Safety of Automated Vehicles: An Empirical Study on Testing Challenges

The technology in the area of automated vehicles is gaining speed and pr...

Alessia Knauss, et al. ∙

research

∙ 01/16/2017

Thompson Sampling For Stochastic Bandits with Graph Feedback

We present a novel extension of Thompson Sampling for stochastic sequent...

Aristide C. Y. Tossou, et al. ∙

research

∙ 01/16/2017

Achieving Privacy in the Adversarial Multi-Armed Bandit

In this paper, we improve the previously best known regret bound to achi...

Aristide C. Y. Tossou, et al. ∙

research

∙ 11/10/2016

Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence

Acquiring your first language is an incredible feat and not easily dupli...

Emilio Jorge, et al. ∙

research

∙ 06/11/2016

Word Sense Disambiguation using a Bidirectional LSTM

In this paper we present a clean, yet effective, model for word sense di...

Mikael Kågebäck, et al. ∙

research

∙ 03/27/2017

LIDAR-based Driving Path Generation Using Fully Convolutional Neural Networks

In this work, a novel learning-based approach has been developed to gene...

Luca Caltagirone, et al. ∙

research

∙ 03/13/2017

Poisson multi-Bernoulli mixture filter: direct derivation and implementation

We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) fi...

Ángel F. García-Fernández, et al. ∙

research

∙ 03/10/2017

Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks

In this work, a deep learning approach has been developed to carry out r...

Luca Caltagirone, et al. ∙

research

∙ 11/27/2015

Algorithms for Differentially Private Multi-Armed Bandits

We present differentially private algorithms for the stochastic Multi-Ar...

Aristide Tossou, et al. ∙

research

∙ 04/22/2015

On the relation between Gaussian process quadratures and sigma-point methods

This article is concerned with Gaussian process quadratures, which are n...

Simo Särkkä, et al. ∙

research

∙ 05/26/2016

Multiple target tracking based on sets of trajectories

This paper proposes the set of target trajectories as the state variable...

Ángel F. García-Fernández, et al. ∙

research

∙ 05/24/2016

Trajectory probability hypothesis density filter

This paper presents the probability hypothesis density (PHD) filter for ...

Ángel F. García-Fernández, et al. ∙

research

∙ 12/10/2014

Generalised Entropy MDPs and Minimax Regret

Bayesian methods suffer from the problem of how to specify prior beliefs...

Emmanouil G. Androulakis, et al. ∙

research

∙ 03/14/2016

Extended Object Tracking: Introduction, Overview and Applications

This article provides an elaborate overview of current research in exten...

Karl Granström, et al. ∙

research

∙ 01/21/2016

Generalized optimal sub-pattern assignment metric

This paper presents the generalized optimal sub-pattern assignment (GOSP...

Abu Sajana Rahmathullah, et al. ∙

research

∙ 10/14/2015

Multiresolution Search of the Rigid Motion Space for Intensity Based Registration

We study the relation between the target functions of low-resolution and...

Behrooz Nasihatkon, et al. ∙

research

∙ 10/25/2012

Performance Evaluation of Random Set Based Pedestrian Tracking Algorithms

The paper evaluates the error performance of three random finite set bas...

Branko Ristic, et al. ∙

research

∙ 12/17/2017

Query-Based Abstractive Summarization Using Neural Networks

In this paper, we present a model for generating summaries of text docum...

Johan Hasselqvist, et al. ∙

research

∙ 12/22/2017

Behavioral software engineering - guidelines for qualitative studies

Researchers are increasingly recognizing the importance of human aspects...

Per Lenberg, et al. ∙

research

∙ 12/21/2017

Practically-Self-Stabilizing Vector Clocks in the Absence of Execution Fairness

Vector clock algorithms are basic wait-free building blocks that facilit...

Iosif Salem, et al. ∙

research

∙ 12/15/2017

Anscombe's Model for Sequential Clinical Trials Revisited

In Anscombe's classical model, the objective is to find the optimal sequ...

Sebastian Jobjörnsson, et al. ∙

research

∙ 11/17/2017

A Supervisory Control Algorithm Based on Property-Directed Reachability

We present an algorithm for synthesising a controller (supervisor) for a...

Koen Claessen, et al. ∙

research

∙ 12/21/2017

Block-Diagonal and LT Codes for Distributed Computing With Straggling Servers

We propose two coded schemes for the distributed computing problem of mu...

Albin Severinson, et al. ∙

research

∙ 11/06/2017

Lisco: A Continuous Approach in LiDAR Point-cloud Clustering

The light detection and ranging (LiDAR) technology allows to sense surro...

Hannaneh Najdataei, et al. ∙

research

∙ 09/18/2017

Searching for test data with feature diversity

There is an implicit assumption in software testing that more diverse an...

Robert Feldt, et al. ∙

research

∙ 02/11/2017

1-bit Massive MU-MIMO Precoding in VLSI

Massive multiuser (MU) multiple-input multiple-output (MIMO) will be a c...

Oscar Castañeda, et al. ∙

research

∙ 09/18/2017

A Novel Approach for Ellipsoidal Outer-Approximation of the Intersection Region of Ellipses in the Plane

In this paper, a novel technique for tight outer-approximation of the in...

Siamak Yousefi, et al. ∙

Chalmers University of Technology

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