Person

Amin Karbasi

This person is no longer with EPFL

Related publications (37)

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Coupled neural associative memories

Mohammad Amin Shokrollahi, Amin Karbasi, Amir Hesam Salavati

We propose a novel architecture to design a neural associative memory that is capable of learning a large number of patterns and recalling them later in presence of noise. It is based on dividing the neurons into local clusters and parallel plains, an arch ...

IEEE2013

Graph-Based Information Processing

Amin Karbasi

We live in a world characterized by massive information transfer and real-time communication. The demand for efficient yet low-complexity algorithms is widespread across different fields, including machine learning, signal processing and communications. Mo ...

EPFL2012

Graph-Constrained Group Testing

Amin Karbasi, Mahdi Cheraghchi Bashi Astaneh, Soheil Mohajerzefreh

Non-adaptive group testing involves grouping arbitrary subsets of

n

items into different pools. Each pool is then tested and defective items are identified. A fundamental question involves minimizing the number of pools required to identify at most

d

d ...

2012

Low-rank Matrix Approximation Using Point-wise Operators

Arash Amini, Amin Karbasi

Extracting low dimensional structure from high dimensional data arises in many applications such as machine learning, statistical pattern recognition, wireless sensor networks, and data compression. If the data is restricted to a lower dimensional subspace ...

Institute of Electrical and Electronics Engineers2012

Multi-Level Error-Resilient Neural Networks

Amin Karbasi, Amir Hesam Salavati

The problem of neural network association is to retrieve a previously memorized pattern from its noisy version using a network of neurons. An ideal neural network should include three components simultaneously: a learning algorithm, a large pattern retriev ...

IEEE2012

Sequential Group Testing with Graph Constraints

Amin Karbasi, Morteza Zadimoghaddam

In conventional group testing, the goal is to detect a small subset of defecting items

\mathcal{D}

in a large population

\mathcal{N}

by grouping \textit{arbitrary} subset of

\mathcal{N}

into different pools. The result of each group test $\mathcal{T} ...

Ieee2012

Comparison-Based Learning with Rank Nets

Amin Karbasi

We consider the problem of search through comparisons, where a user is presented with two candidate objects and reveals which is closer to her intended target. We study adaptive strategies for finding the target, that require knowledge of rank relationship ...

2012

Hot or Not: Interactive Content Search Using Comparisons

Amin Karbasi

In comparison-based active learning, a user searching for a target object navigates through a database in the following manner. The user is asked to select the object most similar to her target from small list of objects. A new object list is then presente ...

2012

Compression with Graphical Constraints: An Interactive Browser

Amin Karbasi, Morteza Zadimoghaddam

We study the problem of navigating/searching through a database of objects with potentially different popularities using a membership oracle. The membership oracle, given a subset of objects

A

, and a target object

t

, determines whether

A

contains

t

...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Calibration in Circular Ultrasound Tomography Devices

Martin Vetterli, Amin Karbasi, Reza Parhizkar

We consider the position calibration problem in circular tomography devices, where sensors deviate from a perfect circle. We introduce a new method of calibration based on the time-of-flight measurements between sensors when the enclosed medium is homogene ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Sequential Group Testing with Graph Constraints

Amin Karbasi, Morteza Zadimoghaddam

In conventional group testing, the goal is to detect a small subset of defecting items

\mathcal{D}

in a large population

\mathcal{N}

by grouping \textit{arbitrary} subset of

\mathcal{N}

into different pools. The result of each group test $\mathcal{T} ...

Ieee2012

Graph-Constrained Group Testing

Amin Karbasi, Mahdi Cheraghchi Bashi Astaneh, Soheil Mohajerzefreh

Non-adaptive group testing involves grouping arbitrary subsets of

n

items into different pools. Each pool is then tested and defective items are identified. A fundamental question involves minimizing the number of pools required to identify at most

d

d ...

2012

Compression with Graphical Constraints: An Interactive Browser

Amin Karbasi, Morteza Zadimoghaddam

We study the problem of navigating/searching through a database of objects with potentially different popularities using a membership oracle. The membership oracle, given a subset of objects

A

, and a target object

t

, determines whether

A

contains

t

...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011