Search Results for author: Reshad Hosseini

Found 28 papers, 12 papers with code

Stochastic First-Order Learning for Large-Scale Flexibly Tied Gaussian Mixture Model

1 code implementation11 Dec 2022 Mohammad Pasande, Reshad Hosseini, Babak Nadjar Araabi

Gaussian Mixture Models (GMMs) are one of the most potent parametric density models used extensively in many applications.

Stochastic Optimization

Fast Online and Relational Tracking

1 code implementation7 Aug 2022 Mohammad Hossein Nasseri, Mohammadreza Babaee, Hadi Moradi, Reshad Hosseini

In this paper, a method for measuring camera motion and removing its effect is presented that efficiently reduces the camera motion effect on tracking.

Multiple Object Tracking

Joint Manifold Learning and Density Estimation Using Normalizing Flows

no code implementations7 Jun 2022 Seyedeh Fatemeh Razavi, Mohammad Mahdi Mehmanchi, Reshad Hosseini, Mostafa Tavassolipour

We propose a single-step method for joint manifold learning and density estimation by disentangling the transformed space obtained by normalizing flows to manifold and off-manifold parts.

Density Estimation

Self-attention Presents Low-dimensional Knowledge Graph Embeddings for Link Prediction

1 code implementation20 Dec 2021 Peyman Baghershahi, Reshad Hosseini, Hadi Moradi

Notably, we yield our promising results with a significant reduction of 66. 9% in the dimensionality of embeddings compared to the five best recent state-of-the-art competitors on average.

Knowledge Graph Embedding Knowledge Graph Embeddings +1

ParsiNorm: A Persian Toolkit for Speech Processing Normalization

1 code implementation1 Nov 2021 Romina Oji, Seyedeh Fatemeh Razavi, Sajjad Abdi Dehsorkh, Alireza Hariri, Hadi Asheri, Reshad Hosseini

Comparison with other available Persian textual normalization tools indicates the superiority of the proposed method in speech processing.

Language Modelling

Solving Viewing Graph Optimization for Simultaneous Position and Rotation Registration

no code implementations29 Aug 2021 Seyed-Mahdi Nasiri, Reshad Hosseini, Hadi Moradi

A viewing graph is a set of unknown camera poses, as the vertices, and the observed relative motions, as the edges.


Optimal Triangulation Method is Not Really Optimal

no code implementations9 Jul 2021 Seyed-Mahdi Nasiri, Reshad Hosseini, Hadi Moradi

Therefore, in contrast to the common practice, we argue that the simple mid-point method should be used in structure-from-motion applications where there is uncertainty in camera parameters.

Accurate and fast matrix factorization for low-rank learning

1 code implementation21 Apr 2021 Reza Godaz, Reza Monsefi, Faezeh Toutounian, Reshad Hosseini

In this paper, we tackle two important problems in low-rank learning, which are partial singular value decomposition and numerical rank estimation of huge matrices.

Matrix Factorization / Decomposition Riemannian optimization

Learning with partially separable data

no code implementations11 Mar 2021 Aida Khozaei, Hadi Moradi, Reshad Hosseini

In this study, we propose a framework for the classification of partially separable data types that are not classifiable using typical methods.

Classification Clustering +1

Reinforcement Learning with Subspaces using Free Energy Paradigm

no code implementations13 Dec 2020 Milad Ghorbani, Reshad Hosseini, Seyed Pooya Shariatpanahi, Majid Nili Ahmadabadi

We propose a free-energy minimization framework for selecting the subspaces and integrate the policy of the state-space into the subspaces.

reinforcement-learning Reinforcement Learning (RL) +1

Contour Integration using Graph-Cut and Non-Classical Receptive Field

1 code implementation27 Oct 2020 Zahra Mousavi Kouzehkanan, Reshad Hosseini, Babak Nadjar Araabi

Many edge and contour detection algorithms give a soft-value as an output and the final binary map is commonly obtained by applying an optimal threshold.

Contour Detection

FRMDN: Flow-based Recurrent Mixture Density Network

no code implementations5 Aug 2020 Seyedeh Fatemeh Razavi, Reshad Hosseini, Tina Behzad

The class of recurrent mixture density networks is an important class of probabilistic models used extensively in sequence modeling and sequence-to-sequence mapping applications.

Deep-RBF Networks Revisited: Robust Classification with Rejection

no code implementations7 Dec 2018 Pourya Habib Zadeh, Reshad Hosseini, Suvrit Sra

On the other hand, deep-RBF networks assign high confidence only to the regions containing enough feature points, but they have been discounted due to the widely-held belief that they have the vanishing gradient problem.

Adversarial Attack Classification +3

Exploiting generalization in the subspaces for faster model-based learning

no code implementations22 Oct 2017 Maryam Hashemzadeh, Reshad Hosseini, Majid Nili Ahmadabadi

Generalization and faster learning in a subspace are due to many-to-one mapping of experiences from the full-space to each state in the subspace.

Decision Making Reinforcement Learning (RL)

An Alternative to EM for Gaussian Mixture Models: Batch and Stochastic Riemannian Optimization

1 code implementation10 Jun 2017 Reshad Hosseini, Suvrit Sra

This motivates us to take a closer look at the problem geometry, and derive a better formulation that is much more amenable to Riemannian optimization.

Density Estimation Riemannian optimization

MixEst: An Estimation Toolbox for Mixture Models

1 code implementation22 Jul 2015 Reshad Hosseini, Mohamadreza Mash'al

Mixture models are powerful statistical models used in many applications ranging from density estimation to clustering and classification.

Clustering Density Estimation +1

Geometric optimisation on positive definite matrices for elliptically contoured distributions

no code implementations NeurIPS 2013 Suvrit Sra, Reshad Hosseini

We exploit the remarkable structure of the convex cone of positive definite matrices which allows one to uncover hidden geodesic convexity of objective functions that are nonconvex in the ordinary Euclidean sense.

Riemannian optimization

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