- Machine-learning-nederland

[jobs] Postdoc Position in Causality for Domain Adaptation and Optimization (University of Amsterdam)
by Joris Mooij 20 Jan '22

20 Jan '22

Vacancy: Postdoc Position in Causality for Domain Adaptation and Optimization (University of Amsterdam) ======================================================================================================= Are you passionate about causality and its applications to domain adaptation and optimization? We have a vacancy for a postdoctoral researcher in the recently established Mercury Machine Learning Lab (MMLL). In this lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) will be working together with data scientists from Booking.com to develop the statistical and machine learning foundations for a new generation of recommendation systems. Motivated by real-world problems faced in industry, we will investigate fundamental problems regarding generalization and bias removal in data analysis, and develop more usable machine learning and reinforcement learning techniques. The successful candidate will be based in the Korteweg-De Vries Institute of the University of Amsterdam, the Netherlands, under supervision of prof. dr. Joris Mooij. Application closing date: February 28, 2022 Preferred starting date: Early 2022 Duration: 4 years For further information, including how to apply, see the official job advertisement at: https://vacatures.uva.nl/UvA/job/Postdoctoral-Position-in-Causality-for-Dom… ------------------------------------------------------------- Joris Mooij Professor in Mathematical Statistics University of Amsterdam http://www.jorismooij.nl/

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Vacancy: Fully funded PhD Position in Causality for Domain Adaptation and Optimization (University of Amsterdam)
by Joris Mooij 10 Jan '22

10 Jan '22

Are you passionate about causality and its applications to domain adaptation and optimization? We have a vacancy for a PhD candidate in the recently established Mercury Machine Learning Lab (MMLL). In this lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) will be working together with data scientists from Booking.com to develop the statistical and machine learning foundations for a new generation of recommendation systems. Motivated by real-world problems faced in industry, we will investigate fundamental problems regarding generalization and bias removal in data analysis, and develop more usable machine learning and reinforcement learning techniques. The successful candidate will be based in the Korteweg-De Vries Institute of the University of Amsterdam, the Netherlands, under supervision of prof. dr. Joris Mooij. Application closing date: January 31, 2022 Preferred starting date: Early 2022 Duration: 4 years For further information, see the official job advertisement at: https://vacatures.uva.nl/UvA/job/PhD-Position-in-Causality-for-Domain-Adapt… ------------------------------------------------------------- Joris Mooij Professor in Mathematical Statistics University of Amsterdam http://www.jorismooij.nl/

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Post-doc position at TU Delft: physics-aware machine learning for clouds and climate
by Franziska Glassmeier 10 Jan '22

10 Jan '22

We invite you to apply for a 1.5-year postdoctoral position in the field of data-driven atmospheric cloud research. Within the scope of physics-aware and interpretable machine learning, you will be free to set your own scientific emphasis. Possible research directions include data-driven model discovery under incorporation of partial physical knowledge such as conservation laws. Examples for applications include boundary-layer clouds and cloud microphysics. As a suitable candidate, you have a background in physics-aware and/or interpretable machine learning, or similar, and at least a basic knowledge of physics. Prior experience with atmospheric science and cloud research is not required. For more details and to apply visit: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?… Your application will be given full consideration if you apply before Jan 17, 2022. ---- TU Delft Franziska Glassmeier Assistant Professor Faculty of Civil Engineering and Geosciences Department Geoscience and Remote Sensing PO Box 5048, 2600 GA Delft, Netherlands f.glassmeier(a)tudelft.nl https://www.tudelft.nl/en/ceg/about-faculty/departments/geoscience-remote-s…

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Post-doc position on Reinforcement Learning in the Real World
by Matthijs Spaan 03 Jan '22

03 Jan '22

Post-doc position (36 months) at Delft University of Technology on reinforcement learning (RL), in collaboration with Booking.com. Potential directions could be causal RL, Bayesian RL, or multiagent RL. Application deadline: Jan 16, 2022 Further details: https://www.academictransfer.com/en/307380/postdoc-on-reinforcement-learnin… For information about this vacancy, please contact Matthijs Spaan and Frans Oliehoek, who will be the supervisors for this position. Cheers, Matthijs

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Call for reading: Robotics, Volume 10, Issue 4 (December 2021) Table of Contents
by Charlene Dong 29 Dec '21

29 Dec '21

/Robotics/ (ISSN 2218-6581, citescore 3.5) Volume 10, Issue 4 (December 2021) Table of Contents (26 articles) https://www.mdpi.com/2218-6581/10/4 *Issue Cover* /Article/: A Robot Architecture Using ContextSLAM to Find Products in Unknown Crowded Retail Environments Daniel Dworakowski, Christopher Thompson, Michael Pham-Hung and Goldie Nejat Robotics 2021, 10(4), 110; doi:10.3390/robotics10040110 (Please note that the title on the cover is slightly different from the article title due to character limitations.) *General* /Article/: A Simulation Study of a Planar Cable-Driven Parallel Robot to Transport Supplies for Patients with Contagious Diseases in Health Care Centers Marco Carpio, Roque Saltaren, Julio Viola, Cecilia García, Juan Guerra, Juan Cely and Cristian Calderón Robotics 2021, 10(4), 111; doi:10.3390/robotics10040111 /Article/: Robot Anticipation Learning System for Ball Catching Diogo Carneiro, Filipe Silva and Petia Georgieva Robotics 2021, 10(4), 113; doi:10.3390/robotics10040113 /Article/: Reuleaux Triangle–Based Two Degrees of Freedom Bipedal Robot Jiteng Yang, Wael Saab, Yujiong Liu and Pinhas Ben-Tzvi Robotics 2021, 10(4), 114; doi:10.3390/robotics10040114 /Article/: Bio-Inspired Conceptual Mechanical Design and Control of a New Human Upper Limb Exoskeleton Narek Zakaryan, Mikayel Harutyunyan and Yuri Sargsyan Robotics 2021, 10(4), 123; doi:10.3390/robotics10040123 /Article/: A Laser Vision System for Relative 3-D Posture Estimation of an Underwater Vehicle with Hemispherical Optics Christos C. Constantinou, George P. Georgiades and Savvas G. Loizou Robotics 2021, 10(4), 126; doi:10.3390/robotics10040126 /Article/: Modal Kinematic Analysis of a Parallel Kinematic Robot with Low-Stiffness Transmissions Paolo Righettini, Roberto Strada and Filippo Cortinovis Robotics 2021, 10(4), 132; doi:10.3390/robotics10040132 /Article/: Overcoming Kinematic Singularities for Motion Control in a Caster Wheeled Omnidirectional Robot Oded Medina and Shlomi Hacohen Robotics 2021, 10(4), 133; doi:10.3390/robotics10040133 /Article/: Multi-Domain Dynamic Modelling of a Low-Cost Upper Limb Rehabilitation Robot Adam G. Metcalf, Justin F. Gallagher, Andrew E. Jackson and Martin C. Levesley Robotics 2021, 10(4), 134; doi:10.3390/robotics10040134 ... *Aerospace Robotics and Autonomous Systems* /Article/: A Mixed-Initiative Formation Control Strategy for Multiple Quadrotors George C. Karras, Charalampos P. Bechlioulis, George K. Fourlas and Kostas J. Kyriakopoulos Robotics 2021, 10(4), 116; doi:10.3390/robotics10040116 /Article/: Dynamically Balanced Pointing System for CubeSats: Study and 3D Printing Manufacturing Nicholas Sesto Gorella, Matteo Caruso, Paolo Gallina and Stefano Seriani Robotics 2021, 10(4), 121; doi:10.3390/robotics10040121 *Industrial Robots & Automation* /Review/: A Suite of Robotic Solutions for Nuclear Waste Decommissioning Ivan Vitanov, Ildar Farkhatdinov, Brice Denoun, Francesca Palermo, Ata Otaran, Joshua Brown, Bukeikhan Omarali, Taqi Abrar, Miles Hansard, Changjae Oh, Stefan Poslad, Chen Liu, Hareesh Godaba, Ketao Zhang, Lorenzo Jamone and Kaspar Althoefer Robotics 2021, 10(4), 112; doi:10.3390/robotics10040112 /Article/: A Low-Cost and Semi-Autonomous Robotic Scanning System for Characterising Radiological Waste Stephen David Monk, Craig West, Manuel Bandala, Nile Dixon, Allahyar Montazeri, C. James Taylor and David Cheneler Robotics 2021, 10(4), 119; doi:10.3390/robotics10040119 *Medical Robotics and Service Robotics* /Article/: A Single-Actuated, Cable-Driven, and Self-Contained Robotic Hand Designed for Adaptive Grasps Negin Nikafrooz and Alexander Leonessa Robotics 2021, 10(4), 109; doi:10.3390/robotics10040109 /Article/: Going Hands-Free: MagnetoSuture™ for Untethered Guided Needle Penetration of Human Tissue Ex Vivo Lamar O. Mair, Sagar Chowdhury, Xiaolong Liu, Onder Erin, Oleg Udalov, Suraj Raval, Benjamin Johnson, Sahar Jafari, David J. Cappelleri, Yancy Diaz-Mercado, Axel Krieger and Irving N. Weinberg Robotics 2021, 10(4), 129; doi:10.3390/robotics10040129 *Intelligent Robots and Mechatronics* /Review/: Personalization and Localization in Human-Robot Interaction: A Review of Technical Methods Mehdi Hellou, Norina Gasteiger, Jong Yoon Lim, Minsu Jang and Ho Seok Ahn Robotics 2021, 10(4), 120; doi:10.3390/robotics10040120 /Article/: Multi-Robot Routing Problem with Min–Max Objective Jennifer David and Thorsteinn Rögnvaldsson Robotics 2021, 10(4), 122; doi:10.3390/robotics10040122 /Article/: Feasibility and Performance Validation of a Leap Motion Controller for Upper Limb Rehabilitation Marcus R. S. B. de Souza, Rogério S. Gonçalves and Giuseppe Carbone Robotics 2021, 10(4), 130; doi:10.3390/robotics10040130 *Sensors and Control in Robotics* /Article/: Inverse Kinematic Control of a Delta Robot Using Neural Networks in Real-Time Akram Gholami, Taymaz Homayouni, Reza Ehsani and Jian-Qiao Sun Robotics 2021, 10(4), 115; doi:10.3390/robotics10040115 /Article/: Topological Analysis of a Novel Compact Omnidirectional Three-Legged Robot with Parallel Hip Structures Regarding Locomotion Capability and Load Distribution David Feller and Christian Siemers Robotics 2021, 10(4), 117; doi:10.3390/robotics10040117 *Special Issues Open for Submissions* https://www.mdpi.com/journal/robotics/special_issues Soft Robotics: Fusing Function with Structure (Deadline: 20 January 2022) Advances in Industrial Robotics and Intelligent Systems (Deadline: 31 January 2022) Advanced Technologies for Autonomous Surgical Robotics (Deadline: 31 January 2022) Fault Diagnosis and Fault-Tolerant Control in Robotic Systems (Deadline: 15 February 2022) Robot Learning: Mapping from Perception to Action (Deadline: 15 February 2022) ... Special Issue Proposal - Open for Application https://www.mdpi.com/journalproposal/sendproposalspecialissue/robotics *Recent Special Issue Reprints* Kinematics and Robot Design I, KaRD2018 Raffaele Di Gregorio (Ed.) ISBN 978-3-0365-1018-7 (Hbk) ; ISBN 978-3-0365-1019-4 (PDF) doi: 10.3390/books978-3-0365-1019-4 Advances in Italian Robotics Giovanni Boschetti, Giulio Rosati and Giuseppe Carbone (Eds.) ISBN 978-3-03928-931-8 (Pbk); ISBN 978-3-03928-932-5 (PDF) doi: 10.3390/books978-3-03928-932-5 Mechanism Design for Robotics Marco Ceccarelli and Alessandro Gasparetto (Eds.) ISBN 978-3-03921-058-9 (Pbk); ISBN 978-3-03921-059-6 (PDF) doi: 10.3390/books978-3-03921-059-6 *Upcoming Partner Conferences* https://www.mdpi.com/journal/robotics/events The 6th International Conference on Data Processing and Robotics (ICDPR 2022) (Sapporo, Japan, 6–8 January 2022) 2022 The 8th International Conference on Mechatronics and Robotics Engineering (Munich, Germany, 10–12 February 2022) 2022 3rd International Conference on Machine Learning and Human-Computer Interaction(MLHMI 2022) (Singapore, 18–20 March 2022) The 14th International Conference on Computer and Automation Engineering 2022 (ICCAE 2022) (Brisbane, Australia, 25–27 March 2022) 2022 the 8th International Conference on Mechatronics System and Robots (ICMSR 2022) (Singapore, 14–16 April 2022) ... 10th *Anniversary* of Robotics: A series of special content and events at https://www.mdpi.com/journal/robotics/anniversary *Awards* Best Paper Award in Special Issue "Women in Robotics" (500CHF) https://www.mdpi.com/journal/robotics/awards/1658 Deadline: 31 August 2022 Robotics 2021–2022 Travel Awards (800 CHF) Application Deadline: 30 June 2022 https://www.mdpi.com/journal/robotics/awards/1057 Robotics 2021–2022 Best Video Abstract Award (500 CHF) https://www.mdpi.com/journal/robotics/awards/1389 Kind regards, Ms. Charlene Dong Managing Editor Email: charlene.dong(a)mdpi.com Robotics (http://www.mdpi.com/journal/robotics/) -- MDPI Branch Office, Beijing Robotics Editorial Office E-Mail: robotics(a)mdpi.com MDPI St. Alban-Anlage 66 4052 Basel, Switzerland http://www.mdpi.com/

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National NeurIPS 2021 debriefing
by Tim van Erven 21 Dec '21

21 Dec '21

Dear Dutch Machine Learners, We're happy to announce that there will once again be an (online)NeurIPS debriefing, wherein PhD students and/or senior researchers will briefly present the paper they found the most interesting atNeurIPS2021. IfNeurIPS is on your radar, we'd like you to consider being one of the presenters. The format is to have 2.5 hours of short talks (15 or 20 minutes, in English). It is not required to have attendedNeurIPS, and you would usually not present your own paper. Talks are generally quite informal, and we like to keep a friendly atmosphere, so this is an ideal opportunity for PhD students to gain experience in presenting. An exact date and schedule will be announced later, but we are currently thinking to set the date in late February or early March. If you are interested in giving a talk or if you have any questions, please email Jack. For up to date information and an overview of past meetings, see www.timvanerven.nl/neurips-debriefing/ <https://eur04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.timvan…> Best regards, Jack J. Mayo <http://jackjmayo.nl> (j.j.mayo(a)uva.nl) Tim van Erven <http://www.timvanerven.nl/> (tim(a)timvanerven.nl) -- Tim van Erven<tim(a)timvanerven.nl> www.timvanerven.nl

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Machine Learning for Regional Climate, Assistant Professorship in
by Marco Loog 19 Dec '21

19 Dec '21

Assistant Professorship in Machine Learning for Regional Climate Tenure track position at Delft University of Technology within the context of its new climate action program. See the vacancy text for details: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?…

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10 years of MDPI Robotics: Join us in the celebration
by Charlene Dong 16 Dec '21

16 Dec '21

*10 years of MDPI Robotics: Join us in the celebration!* Dear Colleagues, We hope this email finds you safe and well! 2021 marks the 10th anniversary of /Robotics/. This is an important milestone for /Robotics/ and a great opportunity to celebrate our history of achievements, highlight our capabilities, and forge our path into the future. Here (https://www.mdpi.com/journal/robotics/anniversary) is the anniversary page, interviews with the chief editors, etc. The goal of this campaign is to stimulate dialogue with you and with our scientific community, sharing our vision for Open Access publishing with the wider world. *Celebration Activities* including: Robotics 2021–2022 Travel Awards Robotics 2021–2022 Best Video Abstract Award *Anniversary Special Issues*: Robotics: 10th Anniversary Feature Papers https://www.mdpi.com/journal/robotics/special_issues/SI_fearure_paper 10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics https://www.mdpi.com/journal/robotics/special_issues/FP_intelligent_mechatr… At the end of 2021, we look forward to joining you in celebrating this exciting journal milestone! Best regards, Charlene Dong Managing Editor Email: charlene.dong(a)mdpi.com Robotics (http://www.mdpi.com/journal/robotics/) -- MDPI Branch Office, Beijing Robotics Editorial Office E-Mail: robotics(a)mdpi.com MDPI St. Alban-Anlage 66 4052 Basel, Switzerland http://www.mdpi.com/ The 2020 CiteScores of Robotics is released and it increased to 3.5 (Ranking Q2 in Control and Optimization category).

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Reinforcement Learning challenge “Patways to Net Zero (carbon emissions)” - Jan 2022
by a.zocca＠vu.nl 13 Dec '21

13 Dec '21

Dear all, On behalf of the organisers, I would like to advertise the following: Reinforcement Learning Challenge, 17th-31st January 2022 The Net Zero Technology Centre, Alan Turing Institute RangL project and Oxquant announce the ‘Pathways to Net Zero’ Reinforcement Learning challenge, which will take place from 17th-31st January 2022. As showcased at COP26 (see the video here), the challenge is to control the rate of deployment of zero-carbon technologies towards net zero UK carbon emissions in 2050. Sign up here to compete as an individual or team. Best, Alessandro ================================= Alessandro Zocca (he/his) Assistant Professor Vrije Universiteit Amsterdam Department of Mathematics https://sites.google.com/site/zoccaale/

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Reminder: Thematic seminar: Samory Kpotufe, Fri November 26, 16h00
by Tim van Erven 25 Nov '21

25 Nov '21

Dear all, The talk by Samory Kpotufe is tomorrow: Our seminar speaker this Friday in the thematic seminar is Samory Kpotufe. Further below, there is also a list of upcoming talks that are scheduled for the second semester. *Samory Kpotufe* (Department of Statistics, Columbia University, http://www.columbia.edu/~skk2175/) Samory works on the intersection between statistics and machine learning, with an interest in adaptive methods, and was one of the chairs for last year's COLT learning theory conference. *Friday November 26*, 16.00-17.00 Online on Zoom: https://uva-live.zoom.us/j/85155421740 Meeting ID: 851 5542 1740 Please also join for online drinks after the talk. *Some Recent Insights on Transfer and Multitask Learning* A common situation in Machine Learning is one where training data is not fully representative of a target population due to bias in the sampling mechanism or due to prohibitive target sampling costs. In such situations, we aim to ’transfer’ relevant information from the training data (a.k.a. source data) to the target application. How much information is in the source data about the target application? Would some amount of target data improve transfer? These are all practical questions that depend crucially on 'how far' the source domain is from the target. However, how to properly measure 'distance' between source and target domains remains largely unclear. In this talk we will argue that much of the traditional notions of 'distance' (e.g. KL-divergence, extensions of TV such as D_A discrepancy, density-ratios, Wasserstein distance) can yield an over-pessimistic picture of transferability. Instead, we show that some asymmetric notions of 'relatedness' between source and target (which we simply term 'transfer-exponents') capture a continuum from easy to hard transfer. Transfer-exponents uncover a rich set of situations where transfer is possible even at fast rates; they encode relative benefits of source and target samples, and have interesting implications for related problems such as 'multi-task or multi-source learning'. In particular, in the case of transfer from multiple sources, we will discuss (if time permits) a strange phenomena: no procedure can guarantee a rate better than that of having a single data source, even in seemingly mild situations where multiple sources are informative about the target. The talk is based on earlier work with Guillaume Martinet, and ongoing work with Steve Hanneke. Seminar organizers: Tim van Erven Botond Szabo https://mschauer.github.io/StructuresSeminar/ *Upcoming talks:* Mar. 11, 2022, *Tomer Koren <https://mschauer.github.io/StructuresSeminar/#Koren>, *Tel Aviv University Mar. 25, 2022, *Nicolò Cesa-Bianchi <https://mschauer.github.io/StructuresSeminar/#CesaBianchi>**, *Università degli Studi di Milano Apr. 8, 2022, *Julia Olkhovskaya <https://sites.google.com/view/julia-olkhovskaya/home>*, Vrije Universiteit Apr. 22, 2022, *Tor Lattimore <https://mschauer.github.io/StructuresSeminar/#Lattimore>*, DeepMind -- Tim van Erven<tim(a)timvanerven.nl> www.timvanerven.nl

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