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researcher

Angshul Majumdar

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV1
  • cs.LG1
  • q-fin.CP1
  • q-fin.ST1
ORCID 0000-0002-1065-3000

identity via Semantic Scholar / OpenAlex

activity
20162023
most citedSuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

q-fin.ST2023

Deep State-Space Model for Predicting Cryptocurrency Price

Shalini Sharma, Angshul Majumdar, Emilie Chouzenoux +1

Our work presents two fundamental contributions. On the application side, we tackle the challenging problem of predicting day-ahead crypto-currency prices. On the methodological si…

q-fin.CP2020★ 1 cited

SuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems

Pooja Gupta, Angshul Majumdar, Emilie Chouzenoux +1

This work proposes a supervised multi-channel time-series learning framework for financial stock trading. Although many deep learning models have recently been proposed in this dom…

cs.LG2016

How to Train Your Deep Neural Network with Dictionary Learning

Vanika Singhal, Shikha Singh, Angshul Majumdar

Currently there are two predominant ways to train deep neural networks. The first one uses restricted Boltzmann machine (RBM) and the second one autoencoders. RBMs are stacked in l…

cs.CV2016

Deep Blind Compressed Sensing

Shikha Singh, Vanika Singhal, Angshul Majumdar

This work addresses the problem of extracting deeply learned features directly from compressive measurements. There has been no work in this area. Existing deep learning tools only…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.