Morteza Haghir Chehreghani is Associate Professor of AI and Machine Learning at Chalmers University of Technology, Department of Computer Science and Engineering, Data Science and AI division. He holds a Ph.D. in Computer Science (AI/Machine Learning group) from ETH Zurich (2014). After the Ph.D., he joined Xerox Research as a Staff Research
Morteza Haghir Chehreghani is Associate Professor of AI and Machine Learning at Chalmers University of Technology, Department of Computer Science and Engineering, Data Science and AI division. He holds a Ph.D. in Computer Science (AI/Machine Learning group) from ETH Zurich (2014).
General information: DC Field Value Language; dc.contributor.author: Carlström, Herman-dc.contributor.author: Slottner Seholm, Filip-dc.contributor.department: Chalmers tekniska Frank-WolfeOptimizationforDominantSetClustering CARLJOHNELL DepartmentofComputerScienceandEngineering ChalmersUniversityofTechnologyandUniversityofGothenburg Abstract Request PDF | A Unified Framework for Online Trip Destination Prediction | Trip destination prediction is an area of increasing importance in many applications such as trip planning, autonomous Morteza Haghir Chehreghani Docent på avdelningen för Data Science och AI, Institutionen för data- och informationsteknik. morteza.chehreghani@chalmers.se +46317726415 Hitta till mig Morteza Haghir Chehreghani Docent på avdelningen för Data Science och AI, Institutionen för data- och informationsteknik. morteza.chehreghani@chalmers.se +46317726415 Hitta till mig Morteza Haghir Chehreghani Associate professor, Data Science and AI division, Department of Computer Science and Engineering. morteza.chehreghani@chalmers.se +46317726415 Find me Chalmers forskningsinformation, projekt och publikationer för Morteza Haghir Chehreghani [12] Morteza Haghir Chehreghani, Mostafa H. Chehreghani, “Modeling Transitivity in Complex Networks”, Thirty-Second Conference on Uncertainty in Artificial Intelligence (UAI), 2016.
He holds a Ph.D. in Computer Science (AI/Machine Learning group) from ETH Zurich (2014). Niklas Akerblom˚ 1;3, Yuxin Chen2 and Morteza Haghir Chehreghani3 1Volvo Car Corporation 2The University of Chicago 3Chalmers University of Technology niklas.akerblom@chalmers.se, chenyuxin@uchicago.edu, morteza.chehreghani@chalmers.se Abstract Energy-efficient navigation constitutes an impor-tant challenge in electric vehicles, due to their lim- Add open access links from to the list of external document links (if available). load links from unpaywall.org. Privacy notice: By enabling the option above, your We propose unsupervised representation learning and feature extraction from dendrograms. The commonly used Minimax distance measures correspond to building a dendrogram with single linkage criterion, with defining specific forms of a level function and a distance function over that. Therefore, we extend this method to arbitrary dendrograms.
Morteza Haghir Chehreghani (academic supervisor) morteza.chehreghani@chalmers.se; Sadegh Rahrovani, (industrial supervisor) sadegh.rahrovani@volvocars.com; Martin Magnusson (Group manager at VolvoCars), martin.m.magnusson@volvocars.com (*) The project is taken and will be conducted by students during spring 2021
morteza.chehreghani@chalmers.se +46317726415 Hitta till mig. Länk till personlig sida.
Online Learning for Energy Efficient Navigation using Contextual Information Master’s thesis in Computer science and engineering YONCA YUNATCI
Part A 41 (5): 1013-1025 (2011) Time Title Student(s) Examiner ; 14:00 - 15:00. Frank-Wolfe Optimization for Dominant Set Clustering (ZOOM: https://chalmers.zoom.us/j/62497622669) 1 2 3 4 c1 1 c1 2 c2 1 1 2 Input layer Concept layer1 Concept layer2 Output layer Dynamic Network Architectures for Deep Q-Learning Modelling Neurogenesis in Generation of Driving Scenario Trajectories with Generative Adversarial Networks Andreas Demetriou, Henrik Allsvåg, Sadegh Rahrovani, Morteza Haghir Chehreghani. itsc 2020: 1-6 [doi] Accelerated proximal incremental algorithm schemes for non-strongly convex functions Ashkan Panahi, Morteza Haghir Chehreghani, Devdatt P. Dubhashi.
Syst. Man Cybern. Part A 41 (5): 1013-1025 (2011)
Morteza Haghir Chehreghani is Associate Professor of AI and Machine Learning at Chalmers University of Technology, Department of Computer Science and Engineering, Data Science and AI division. He holds a Ph.D. in Computer Science (AI/Machine Learning group) from ETH Zurich (2014). Niklas Akerblom˚ 1;3, Yuxin Chen2 and Morteza Haghir Chehreghani3 1Volvo Car Corporation 2The University of Chicago 3Chalmers University of Technology niklas.akerblom@chalmers.se, chenyuxin@uchicago.edu, morteza.chehreghani@chalmers.se Abstract Energy-efficient navigation constitutes an impor-tant challenge in electric vehicles, due to their lim-
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in Computer Science (AI/Machine Learning group) from ETH Zurich (2014).
in Computer Science (AI/Machine Learning group) from ETH Zurich (2014). Morteza Haghir Chehreghani is Associate Professor of AI and Machine Learning at Chalmers University of Technology, Department of Computer Science and Engineering, Data Science and AI division.
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PhD Student of Computer Science, Chalmers University of Technology - Citerat av 7 A Rahbar, A Panahi, C Bhattacharyya, D Dubhashi, MH Chehreghani.
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Chalmers University of Technology - Cited by 575 - Artificial Intelligence - Machine Learning - Data Science
This work was Correspondence to Morteza Haghir Chehreghani. Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani Energy-efficient navigation constitutes an important challenge in electric vehicles, due to their limited Sep 25, 2020 sadegh.rahrovani@volvocars.com. Morteza Haghir Chehreghani. Department of Computer Engineering. Chalmers University of Technology. Emilio Jorge. Chalmers University PhD student.