Ehsan Amid
Ehsan Amid
Research Scientist at Google
Verified email at - Homepage
Cited by
Cited by
Multiview triplet embedding: Learning attributes in multiple maps
E Amid, A Ukkonen
International Conference on Machine Learning, 1472-1480, 2015
Robust bi-tempered logistic loss based on bregman divergences
E Amid, MK Warmuth, R Anil, T Koren
Advances in Neural Information Processing Systems 32 pre-proceedings …, 2019
A kernel-learning approach to semi-supervised clustering with relative distance comparisons
E Amid, A Gionis, A Ukkonen
European Conference on Machine Learning and Principles and Practice of …, 2015
A fast method of steel surface defect detection using decision trees applied to LBP based features
SR Aghdam, E Amid, MF Imani
2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA …, 2012
Unsupervised feature extraction for multimedia event detection and ranking using audio content
E Amid, A Mesaros, KJ Palomäki, J Laaksonen, M Kurimo
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
Enhanced Performance for Support Vector Machines as Multiclass Classifiers in Steel Surface Defect Detection
E Amid, SR Aghdam, H Amindavar
International Journal of Electrical and Computer Engineering 6 (7), 693-697, 2012
TriMap: Large-scale dimensionality reduction using triplets
E Amid, MK Warmuth
arXiv preprint arXiv:1910.00204, 2019
PicSOM Experiments in TRECVID 2013.
S Ishikawa, M Koskela, M Sjöberg, J Laaksonen, E Oja, E Amid, ...
A more globally accurate dimensionality reduction method using triplets
E Amid, MK Warmuth
arXiv preprint arXiv:1803.00854, 2018
Semi-supervised kernel metric learning using relative comparisons
E Amid, A Gionis, A Ukkonen
arXiv preprint arXiv:1612.00086, 2016
Winnowing with Gradient Descent
E Amid, MK Warmuth
Conference on Learning Theory (COLT), 2020
Two-temperature logistic regression based on the Tsallis divergence
E Amid, MK Warmuth, S Srinivasan
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Reparameterizing Mirror Descent as Gradient Descent
E Amid, MK Warmuth
Advances in Neural Information Processing Systems 33 pre-proceedings …, 2020
Low-dimensional data embedding via robust ranking
E Amid, N Vlassis, MK Warmuth
arXiv preprint arXiv:1611.09957, 2016
An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint
E Amid, MK Warmuth
AAAI Conference on Artificial Intelligence, 2020
Divergence-based motivation for online EM and combining hidden variable models
E Amid, MK Warmuth
UAI: Uncertainty in Artificial Intelligence, 2020
Rank-smoothed Pairwise Learning in Perceptual Quality Assessment
H Talebi, E Amid, P Milanfar, MK Warmuth
IEEE International Conference on Image Processing, 2020
Optimizing the Information Retrieval Trade-off in Data Visualization Using -Divergence
E Amid, O Dikmen, E Oja
arXiv preprint arXiv:1505.05821, 2015
Musical instrument classification using embedded hidden Markov models
E Amid, SR Aghdam
International Journal of Electrical and Computer Engineering 6 (7), 678-683, 2012
A case where a spindly two-layer linear network whips any neural network with a fully connected input layer
MK Warmuth, W Kotłowski, E Amid
Algorithmic Learning Theory 2021, 2020
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