Saikat Chatterjee

Orcid: 0000-0003-2886-8605

According to our database1, Saikat Chatterjee authored at least 160 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
DeepBayes - An estimator for parameter estimation in stochastic nonlinear dynamical models.
Autom., January, 2024

DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Learning Setup.
IEEE Trans. Signal Process., 2024

Data-driven Bayesian State Estimation with Compressed Measurement of Model-free Process using Semi-supervised Learning.
CoRR, 2024

IMU-based Online Multi-lidar Calibration.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

DeePMOS-$\mathcal{B}$: Deep Posterior Mean-Opinion-Score Using Beta Distribution.
Proceedings of the 32nd European Signal Processing Conference, 2024

2023
Extension of Topological Groupoids and Hurewicz Morphisms.
Appl. Categorical Struct., October, 2023

Observability-Aware Online Multi-Lidar Extrinsic Calibration.
IEEE Robotics Autom. Lett., May, 2023

Identifying and analysing toxic actors and communities on Facebook by employing network analysis.
CoRR, 2023

Automated Sentiment and Hate Speech Analysis of Facebook Data by Employing Multilingual Transformer Models.
CoRR, 2023

M-LIO: Multi-lidar, multi-IMU odometry with sensor dropout tolerance.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

DeePMOS: Deep Posterior Mean-Opinion-Score of Speech.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Compressed Sensing of Generative Sparse-Latent (GSL) Signals.
Proceedings of the 31st European Signal Processing Conference, 2023

DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Bayesian Setup.
Proceedings of the 31st European Signal Processing Conference, 2023

Latent-Based Neural Net for Non-Intrusive Speech Quality Assessment.
Proceedings of the 31st European Signal Processing Conference, 2023

2022
Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms.
J. Digit. Imaging, 2022

AERO: Design Space Exploration Framework for Resource-Constrained CNN Mapping on Tile-Based Accelerators.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2022

Multi-modal curb detection and filtering.
CoRR, 2022

Decentralized learning of randomization-based neural networks with centralized equivalence.
Appl. Soft Comput., 2022

Neural Greedy Pursuit for Feature Selection.
Proceedings of the International Joint Conference on Neural Networks, 2022

Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Deterministic Transform Based Weight Matrices for Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2022

Time-varying Normalizing Flow for Generative Modeling of Dynamical Signals.
Proceedings of the 30th European Signal Processing Conference, 2022

2021
Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with Explainability.
CoRR, 2021

Asynchronous Decentralized Learning of Randomization-Based Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2021

Detecting Signal Corruptions in Voice Recordings For Speech Therapy.
Proceedings of the IEEE International Conference on Acoustics, 2021

Feature Reuse for a Randomization Based Neural Network.
Proceedings of the IEEE International Conference on Acoustics, 2021

A ReLU Dense Layer to Improve the Performance of Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2021

Use of Deterministic Transforms to Design Weight Matrices of a Neural Network.
Proceedings of the 29th European Signal Processing Conference, 2021

2020
Online Spatiotemporal Popularity Learning via Variational Bayes for Cooperative Caching.
IEEE Trans. Commun., 2020

High-dimensional neural feature design for layer-wise reduction of training cost.
EURASIP J. Adv. Signal Process., 2020

Statistical model-based evaluation of neural networks.
CoRR, 2020

Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University.
CoRR, 2020

Asynchronous Decentralized Learning of a Neural Network.
CoRR, 2020

Robust Classification Using Hidden Markov Models and Mixtures of Normalizing Flows.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Neural Network based Explicit Mixture Models and Expectation-maximization based Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Recursive Prediction of Graph Signals With Incoming Nodes.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Gaussian Processes Over Graphs.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Asynchrounous Decentralized Learning of a Neural Network.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

High-Dimensional Neural Feature Using Rectified Linear Unit And Random Matrix Instance.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Hidden Markov Models for Sepsis Detection in Preterm Infants.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Design of a Non-negative Neural Network to Improve on NMF.
Proceedings of the 28th European Signal Processing Conference, 2020

Learning without Forgetting for Decentralized Neural Nets with Low Communication Overhead.
Proceedings of the 28th European Signal Processing Conference, 2020

Adaptive Learning without Forgetting via Low-Complexity Convex Networks.
Proceedings of the 28th European Signal Processing Conference, 2020

Powering Hidden Markov Model by Neural Network Based Generative Models.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Dual sentence representation model integrating prior knowledge for bio-text-mining.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019
Predicting Graph Signals Using Kernel Regression Where the Input Signal is Agnostic to a Graph.
IEEE Trans. Signal Inf. Process. over Networks, 2019

Estimate exchange over network is good for distributed hard thresholding pursuit.
Signal Process., 2019

On Hilbert transform, analytic signal, and modulation analysis for signals over graphs.
Signal Process., 2019

SSFN: Self Size-estimating Feed-forward Network and Low Complexity Design.
CoRR, 2019

Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise.
Proceedings of the IEEE International Conference on Acoustics, 2019

Entropy-regularized Optimal Transport Generative Models.
Proceedings of the IEEE International Conference on Acoustics, 2019

α Belief Propagation as Fully Factorized Approximation.
Proceedings of the 2019 IEEE Global Conference on Signal and Information Processing, 2019

Convex Optimization Based Sparse Learning Over Networks.
Proceedings of the 27th European Signal Processing Conference, 2019

LOSoft: ℓ0 Minimization via Soft Thresholding.
Proceedings of the 27th European Signal Processing Conference, 2019

2018
Sparse Signal Recovery Using Iterative Proximal Projection.
IEEE Trans. Signal Process., 2018

Greedy Sparse Learning Over Network.
IEEE Trans. Signal Inf. Process. over Networks, 2018

Supervised Linear Regression for Graph Learning from Graph Signals.
CoRR, 2018

Locally Convex Sparse Learning over Networks.
CoRR, 2018

R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network.
CoRR, 2018

Mutual Information Preserving Analysis of a Single Layer Feedforward Network.
Proceedings of the 15th International Symposium on Wireless Communication Systems, 2018

Multi-Kernel Regression for Graph Signal Processing.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Distributed Large Neural Network with Centralized Equivalence.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Extreme Learning Machine for Graph Signal Processing.
Proceedings of the 26th European Signal Processing Conference, 2018

2017
Generalized fusion algorithm for compressive sampling reconstruction and RIP-based analysis.
Signal Process., 2017

Large Neural Network Based Detection of Apnea, Bradycardia and Desaturation Events.
CoRR, 2017

Progressive Learning for Systematic Design of Large Neural Networks.
CoRR, 2017

Kernel Regression for Signals over Graphs.
CoRR, 2017

Distributed greedy sparse learning over doubly stochastic networks.
Proceedings of the 25th European Signal Processing Conference, 2017

A connectedness constraint for learning sparse graphs.
Proceedings of the 25th European Signal Processing Conference, 2017

2016
Design and Analysis of a Greedy Pursuit for Distributed Compressed Sensing.
IEEE Trans. Signal Process., 2016

Relevance Singular Vector Machine for Low-Rank Matrix Reconstruction.
IEEE Trans. Signal Process., 2016

Analysis of Regularized LS Reconstruction and Random Matrix Ensembles in Compressed Sensing.
IEEE Trans. Inf. Theory, 2016

Alternating strategies with internal ADMM for low-rank matrix reconstruction.
Signal Process., 2016

Hilbert Transform, Analytic Signal, and Modulation Analysis for Graph Signal Processing.
CoRR, 2016

Automatic Recognition of Social Roles Using Long Term Role Transitions in Small Group Interactions.
Proceedings of the 17th Annual Conference of the International Speech Communication Association, 2016

Bayesian Cramer-Rao bounds for factorized model based low rank matrix reconstruction.
Proceedings of the 24th European Signal Processing Conference, 2016

2015
Bayesian Learning for Low-Rank matrix reconstruction.
CoRR, 2015

Greedy minimization of l1-norm with high empirical success.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Universal algorithm for compressive sampling.
Proceedings of the 23rd European Signal Processing Conference, 2015

Graph linear prediction results in smaller error than standard linear prediction.
Proceedings of the 23rd European Signal Processing Conference, 2015

Bayesian learning for robust principal component analysis.
Proceedings of the 23rd European Signal Processing Conference, 2015

Bayesian learning for time-varying linear prediction of speech.
Proceedings of the 23rd European Signal Processing Conference, 2015

A 65 nm standard cell library for ultra low-power applications.
Proceedings of the European Conference on Circuit Theory and Design, 2015

2014
Estimation for the Linear Model With Uncertain Covariance Matrices.
IEEE Trans. Signal Process., 2014

Joint Source-Channel Vector Quantization for Compressed Sensing.
IEEE Trans. Signal Process., 2014

A Committee Machine Approach for Compressed Sensing Signal Reconstruction.
IEEE Trans. Signal Process., 2014

Distributed greedy pursuit algorithms.
Signal Process., 2014

Dirichlet mixture modeling to estimate an empirical lower bound for LSF quantization.
Signal Process., 2014

Progressive fusion of reconstruction algorithms for low latency applications in compressed sensing.
Signal Process., 2014

Methods for Distributed Compressed Sensing.
J. Sens. Actuator Networks, 2014

Analysis of Democratic Voting Principles used in Distributed Greedy Algorithms.
CoRR, 2014

DIPP - Distributed Parallel Pursuit.
CoRR, 2014

Relevance Singular Vector Machine for low-rank matrix sensing.
CoRR, 2014

Distributed Quantization for Measurement of Correlated Sparse Sources over Noisy Channels.
CoRR, 2014

Alternating Strategies Are Good For Low-Rank Matrix Reconstruction.
CoRR, 2014

SEK: sparsity exploiting <i>k</i>-mer-based estimation of bacterial community composition.
Bioinform., 2014

A sparsity based preprocessing for noise robust speech recognition.
Proceedings of the 2014 IEEE Spoken Language Technology Workshop, 2014

Reduced Look Ahead Orthogonal Matching Pursuit.
Proceedings of the Twentieth National Conference on Communications, 2014

Distributed quantization for compressed sensing.
Proceedings of the IEEE International Conference on Acoustics, 2014

Combined modeling of sparse and dense noise improves Bayesian RVM.
Proceedings of the 22nd European Signal Processing Conference, 2014

Piecewise Toeplitz matrices-based sensing for rank minimization.
Proceedings of the 22nd European Signal Processing Conference, 2014

2013
Analysis-by-Synthesis Quantization for Compressed Sensing Measurements.
IEEE Trans. Signal Process., 2013

The Linear Model Under Mixed Gaussian Inputs: Designing the Transfer Matrix.
IEEE Trans. Signal Process., 2013

Fusion of Algorithms for Compressed Sensing.
IEEE Trans. Signal Process., 2013

Line spectrum estimation with probabilistic priors.
Signal Process., 2013

Iteratively reweighted least squares for reconstruction of low-rank matrices with linear structure.
Proceedings of the IEEE International Conference on Acoustics, 2013

Distributed predictive subspace pursuit.
Proceedings of the IEEE International Conference on Acoustics, 2013

Analysis-by-synthesis-based quantization of compressed sensing measurements.
Proceedings of the IEEE International Conference on Acoustics, 2013

Channel-optimized vector quantizer design for compressed sensing measurements.
Proceedings of the IEEE International Conference on Acoustics, 2013

Pilot design for MIMO channel estimation: An alternative to the Kronecker structure assumption.
Proceedings of the IEEE International Conference on Acoustics, 2013

Parallel pursuit for distributed compressed sensing.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Statistical mechanics approach to sparse noise denoising.
Proceedings of the 21st European Signal Processing Conference, 2013

Conditional prior based lmmse estimation of sparse signals.
Proceedings of the 21st European Signal Processing Conference, 2013

Enhanced Capon beamformer using regularized covariance matching.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

2012
Dynamic Iterative Pursuit.
IEEE Trans. Signal Process., 2012

On MMSE Estimation: A Linear Model Under Gaussian Mixture Statistics.
IEEE Trans. Signal Process., 2012

Projection-Based and Look-Ahead Strategies for Atom Selection.
IEEE Trans. Signal Process., 2012

Alternating Least-Squares for Low-Rank Matrix Reconstruction.
IEEE Signal Process. Lett., 2012

Typical l<sub>1</sub>-recovery limit of sparse vectors represented by concatenations of random orthogonal matrices
CoRR, 2012

Fusion of Matching Pursuits for Compressed Sensing Signal Reconstruction
CoRR, 2012

FROGS: A serial reversible greedy search algorithm.
Proceedings of the 2012 Swedish Communication Technologies Workshop, Swe-CTW 2012, Lund, 2012

Analysis of sparse representations using bi-orthogonal dictionaries.
Proceedings of the 2012 IEEE Information Theory Workshop, 2012

Performance bounds for vector quantized compressive sensing.
Proceedings of the International Symposium on Information Theory and its Applications, 2012

Dynamic subspace pursuit.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

A greedy pursuit algorithm for distributed compressed sensing.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Detection of sparse random signals using compressive measurements.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Fusion of Greedy Pursuits for compressed sensing signal reconstruction.
Proceedings of the 20th European Signal Processing Conference, 2012

2011
Auditory Model-Based Design and Optimization of Feature Vectors for Automatic Speech Recognition.
IEEE Trans. Speech Audio Process., 2011

Look ahead parallel pursuit.
Proceedings of the 2011 IEEE Swedish Communication Technologies Workshop, 2011

Analysis of MMSE estimation for compressive sensing of block sparse signals.
Proceedings of the 2011 IEEE Information Theory Workshop, 2011

Gaussian mixture modeling for source localization.
Proceedings of the IEEE International Conference on Acoustics, 2011

Look ahead orthogonal matching pursuit.
Proceedings of the IEEE International Conference on Acoustics, 2011

Greedy pursuits for compressed sensing of jointly sparse signals.
Proceedings of the 19th European Signal Processing Conference, 2011

Hybrid greedy pursuit.
Proceedings of the 19th European Signal Processing Conference, 2011

2010
On the use of compressive sampling for wide-band spectrum sensing.
Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, 2010

Statistical post-processing improves basis pursuit denoising performance.
Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, 2010

A ratification of means: international law and assistive technology in the developing world.
Proceedings of the 4th ACM/IEEE International Conference on Information and Communication Technologies and Development, 2010

Selecting static and dynamic features using an advanced auditory model for speech recognition.
Proceedings of the IEEE International Conference on Acoustics, 2010

Auditory model based modified MFCC features.
Proceedings of the IEEE International Conference on Acoustics, 2010

Structured Gaussian mixture model based product VQ.
Proceedings of the 18th European Signal Processing Conference, 2010

2009
Reduced complexity two stage vector quantization.
Digit. Signal Process., 2009

Auditory model based optimization of MFCCs improves automatic speech recognition performance.
Proceedings of the 10th Annual Conference of the International Speech Communication Association, 2009

Analysis-by-synthesis based switched transform domain split VQ using Gaussian mixture model.
Proceedings of the IEEE International Conference on Acoustics, 2009

2008
Optimum Transform Domain Split VQ.
IEEE Signal Process. Lett., 2008

Predicting VQ Performance Bound for LSF Coding.
IEEE Signal Process. Lett., 2008

Switched Conditional PDF-Based Split VQ Using Gaussian Mixture Model.
IEEE Signal Process. Lett., 2008

Optimum switched split vector quantization of LSF parameters.
Signal Process., 2008

Subspace based speech enhancement using Gaussian mixture model.
Proceedings of the 9th Annual Conference of the International Speech Communication Association, 2008

GMM based Bayesian approach to speech enhancement in signal / transform domain.
Proceedings of the IEEE International Conference on Acoustics, 2008

Speech enhancement using intra-frame dependency in DCT domain.
Proceedings of the 2008 16th European Signal Processing Conference, 2008

Low complexity wideband LSF quantization using GMM of uncorrelated Gaussian mixtures.
Proceedings of the 2008 16th European Signal Processing Conference, 2008

2007
Analysis of Conditional PDF-Based Split VQ.
IEEE Signal Process. Lett., 2007

Conditional PDF-Based Split Vector Quantization of Wideband LSF Parameters.
IEEE Signal Process. Lett., 2007

Joint inter-frame and intra-frame predictive coding of LSF parameters.
Proceedings of the 9th International Symposium on Signal Processing and Its Applications, 2007

Computationally efficient optimum weighting function for vector quantization of LSF parameters.
Proceedings of the 9th International Symposium on Signal Processing and Its Applications, 2007

Normalized two stage SVQ for minimum complexity wide-band LSF quantization.
Proceedings of the 8th Annual Conference of the International Speech Communication Association, 2007

Sequential Split Vector Quantization of LSF Parameters using Conditional Pdf.
Proceedings of the IEEE International Conference on Acoustics, 2007

2006
Comparison of prediction based LSF quantization methods using split VQ.
Proceedings of the Ninth International Conference on Spoken Language Processing, 2006

Two stage transform vector quantization of LSFs for wideband speech coding.
Proceedings of the Ninth International Conference on Spoken Language Processing, 2006


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