activity
20182020
most citedActive Learning of Causal Structures with Deep Reinforcement Learning

1 citations · 2 across the 3 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

cs.DC2020

High-Throughput Parallel Viterbi Decoder on GPU Tensor Cores

Alireza Mohammadidoost, Matin Hashemi

Many research works have been performed on implementation of Vitrerbi decoding algorithm on GPU instead of FPGA because this platform provides considerable flexibility in addition…

cs.DC20201 cited

High-Throughput and Memory-Efficient Parallel Viterbi Decoder for Convolutional Codes on GPU

Alireza Mohammadidoost, Matin Hashemi

This paper describes a parallel implementation of Viterbi decoding algorithm. Viterbi decoder is widely used in many state-of-the-art wireless systems. The proposed solution optimi…

cs.AI20201 cited

Active Learning of Causal Structures with Deep Reinforcement Learning

Amir Amirinezhad, Saber Salehkaleybar, Matin Hashemi

We study the problem of experiment design to learn causal structures from interventional data. We consider an active learning setting in which the experimenter decides to intervene…

eess.SP2020

Deep-Learning Based Blind Recognition of Channel Code Parameters over Candidate Sets under AWGN and Multi-Path Fading Conditions

Sepehr Dehdashtian, Matin Hashemi, Saber Salehkaleybar

We consider the problem of recovering channel code parameters over a candidate set by merely analyzing the received encoded signals. We propose a deep learning-based solution that…

cs.DC2020

gIM: GPU Accelerated RIS-based Influence Maximization Algorithm

Soheil Shahrouz, Saber Salehkaleybar, Matin Hashemi

Given a social network modeled as a weighted graph , the influence maximization problem seeks vertices to become initially influenced, to maximize the expected number of inf…