Please see my updated personal webpage
I received my PhD student in Computer Science from UCSC in June 2020. My advisor is Prof. Manfred K. Warmuth. My research focuses on machine learning, metric learning, clustering, and recently, computational learning theory.
E. Amid and M. K. Warmuth, "Two-temperature logistic regression based on the Tsallis divergence", submitted to AISTATS, 2018.
E. Amid, M. K. Warmuth, and N. Vlassis, "Low-dimensional Data Emebdding via Robust Raning", submitted to the Web Conf, 2018.
E. Amid, A. Gionis, and A. Ukkonen, "A kernel-learning approach to semi-supervised clustering with relative distance comparisons", in ECML PKDD, 2015.
E. Amid, A. Ukkonen, "Multiview Triplet Embedding: Learning Attributes in Multiple Maps", in International Conference on Machine Learning (ICML), 2015.
E. Amid, O. Dikmen, E. Oja, "Optimizing the Information Retrieval Trade-off in Data Visualization Using α-Divergence," arXiv preprint arXiv:1505.05821, 2015. pdf
E. Amid, A. Mesaros, K. J. Palomäki, J. Laaksonen, M. Kurimo, "Unsupervised Feature Extraction for Multimedia Event Detection and Ranking Using Audio Content," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014. pdf
S. Ishikawa, M. Koskela, M. Sjöberg, J. Laaksonen, E. Oja, E. Amid, K. J. Palomäki, A. Mesaros, M. Kurimo, "PicSOM Experiments in TRECVID 2013," Proceedings of the TRECVID 2013 Workshop, 2013. pdf
E. Amid, "Bayesian Non-parametric Image Segmentation with Markov Random Field Prior," Image Analysis, pp. 76-84, 2013. pdf
S. Rezaei Aghdam, E. Amid, M. Faghih Imani, "A Fast Method of Steel Surface Defect Detection Using Decision Trees Applied to LBP Based Features," IEEE Conference on Industrial Electronics and Applications (ICIEA), 2012. pdf
E. Amid, S. Rezaei Aghdam, H. Amindavar, "Enhanced Performance for Support Vector Machines as Multi-class Classifiers in Steel Surface Defect Detection," World Academy of Science, Engineering and Technology, pp. 1096-1100, 2012. pdf
E. Amid, S. Rezaei Aghdam, "Musical Instrument Classification Using Embedded Hidden Markov Models," World Academy of Science, Engineering and Technology, pp. 601-606, 2012. pdfTheses:
M.Sc. Thesis: "Application of α-Divergence for Stochastic Neighbor Embedding in Data Visualization" pdf
B.Sc. Thesis: "Musical Instrument Classification Using Statistical Models"
Data Scientist, Microsoft Bing Ads, June-Sep. 2017
Data Scientist, Adobe Research, June-Nov. 2016
CMPS 242: Introduction to Machine Learning
(Lectured by Prof. Manfred K. Warmuth)
Spring 2017: CMPS 142: Machine Learning and Data Mining
Spring 2015: T-61.6030 Dynamical Models for Prediction and Decision Making (Lectured by Prof. Jaakko Hollmén)
Spring 2015: T-61.5010 Information Visualization (Lectured by Prof. Pekka Marttinen)
Fall 2014: T-61.3050 Machine Learning: Basic Principles (Lectured by Prof. Erkki Oja)
Spring 2014: T-61.3025 Principles of Pattern Recognition (Lectured by Prof. Erkki Oja)
Spring 2012: Workshop on Signal Processing with MATLAB (at Tehran Polytechnic)
Last modified 21-October-2017.