Publications by Amin Karbasi | EPFL Graph Search

Learning Neural Connectivity from Firing Activity: Scalable Algorithms with Provable Guarantees

Martin Vetterli, Amin Karbasi, Amir Hesam Salavati

The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network’ ...

Springer New York LLC2018

Learning Network Structures from Firing Patterns

Martin Vetterli, Amin Karbasi, Amir Hesam Salavati

How can we decipher the hidden structure of a network based on limited observations? This question arises in many scenarios ranging from social to wireless and to neural networks. In such settings, we typically observe the nodes’ behaviors (e.g., the time ...

Ieee2016

Asynchronous Decoding of LDPC Codes over BEC

Amin Karbasi, Amir Hesam Salavati, Saeid Haghighatshoar

LDPC codes are typically decoded by running a synchronous message passing algorithm over the corresponding bipartite factor graph (made of variable and check nodes). More specifically, each synchronous round consists of 1) updating all variable nodes based ...

2015

Noise facilitation in associative memories of exponential capacity

Mohammad Amin Shokrollahi, Amin Karbasi, Amir Hesam Salavati

Recent advances in associative memory design through structured pattern sets and graph-based inference al- gorithms have allowed reliable learning and recall of an exponential number of patterns. Although these designs correct external errors in recall, th ...

Mit Press2014

Near-Optimally Teaching the Crowd to Classify

Andreas Krause, Amin Karbasi, Ilija Bogunovic

How should we present training examples to learners to teach them classification rules? This is a natural problem when training workers for crowdsourcing labeling tasks, and is also moti- vated by challenges in data-driven online educa- tion. We propose a ...

2014

Constrained Binary Identification Problem

Amin Karbasi, Morteza Zadimoghaddam

We consider the problem of building a binary decision tree, to locate an object within a set by way of the least number of membership queries. This problem is equivalent to the “20 questions game” of information theory and is closely related to lossless so ...

2013

Calibration Using Matrix Completion with Application to Ultrasound Tomography

Martin Vetterli, Amin Karbasi, Reza Parhizkar

We study the calibration process in circular ultrasound tomography devices where the sensor positions deviate from the circumference of a perfect circle. This problem arises in a variety of applications in signal processing ranging from breast imaging to s ...

Institute of Electrical and Electronics Engineers2013

Robust Localization from Incomplete Local Information

Amin Karbasi

We consider the problem of localizing wireless devices in an ad-hoc network embedded in a

d

-dimensional Euclidean space. Obtaining a good estimation of where wireless devices are located is crucial in wireless network applications including environment m ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Iterative Learning and Denoising in Convolutional Neural Associative Memories

Mohammad Amin Shokrollahi, Amin Karbasi, Amir Hesam Salavati

The task of a neural associative memory is to retrieve a set of previously memorized pat- terns from their noisy versions by using a net- work of neurons. Hence, an ideal network should be able to 1) gradually learn a set of patterns, 2) retrieve the corre ...

2013

Noise-enhanced associative memories

Mohammad Amin Shokrollahi, Amin Karbasi, Amir Hesam Salavati

Recent advances in associative memory design through structured pattern sets and graph-based inference algorithms have allowed reliable learning and recall of an exponential number of patterns. Although these designs correct external errors in recall, they ...

2013

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Learning Neural Connectivity from Firing Activity: Scalable Algorithms with Provable Guarantees

Learning Network Structures from Firing Patterns

Asynchronous Decoding of LDPC Codes over BEC

Noise facilitation in associative memories of exponential capacity

Near-Optimally Teaching the Crowd to Classify

Constrained Binary Identification Problem

Calibration Using Matrix Completion with Application to Ultrasound Tomography

Robust Localization from Incomplete Local Information

Iterative Learning and Denoising in Convolutional Neural Associative Memories

Noise-enhanced associative memories

Learning Neural Connectivity from Firing Activity: Scalable Algorithms with Provable Guarantees

Learning Network Structures from Firing Patterns

Asynchronous Decoding of LDPC Codes over BEC

Constrained Binary Identification Problem

Noise facilitation in associative memories of exponential capacity

Noise-enhanced associative memories

Calibration Using Matrix Completion with Application to Ultrasound Tomography

Near-Optimally Teaching the Crowd to Classify

Robust Localization from Incomplete Local Information

Iterative Learning and Denoising in Convolutional Neural Associative Memories