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ICASSP 2021

ICASSP 2021 - IEEE International Conference on Acoustics, Speech and Signal Processing is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The ICASSP 2021 conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world. Visit website.

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[Poster] A Global Cayley Parametrization of Stiefel Manifold for Direct Utilization of Optimization Mechanisms Over Vector Spaces
Robust self-supervised speaker representation learning via instance mix regularization
COOPNET: MULTI-MODAL COOPERATIVE GENDER PREDICTION IN SOCIAL MEDIA USER PROFILING
Convex Neural Autoregressive Models: Towards Tractable, Expressive, and Theoretically-Backed Models for Sequential Forecasting and Prediction
SCALABLE REINFORCEMENT LEARNING FOR ROUTING IN AD-HOC NETWORKS BASED ON PHYSICAL-LAYER ATTRIBUTES
CONTROL ARCHITECTURE OF THE DOUBLE-CROSS-CORRELATION PROCESSOR FOR SAMPLING-RATE-OFFSET ESTIMATION IN ACOUSTIC SENSOR NETWORKS
HEBBNET: A SIMPLIFIED HEBBIAN LEARNING FRAMEWORK TO DO BIOLOGICALLY PLAUSIBLE LEARNING
MODIFIED ARCSINE LAW FOR ONE-BIT SAMPLED STATIONARY SIGNALS WITH TIME-VARYING THRESHOLDS
Optimizing Short-Time Fourier Transform Parameters via Gradient Descent
Distributed Scheduling Using Graph Neural Networks
FULL-DUPLEX MULTIFUNCTION TRANSCEIVER WITH JOINT CONSTANT ENVELOPE TRANSMISSION AND WIDEBAND RECEPTION // ICASSP 2021 poster
SPARSE-CODED DYNAMIC MODE DECOMPOSITION ON GRAPH FOR PREDICTION OF RIVER WATER LEVEL DISTRIBUTION
G-ARRAYS: GEOMETRIC ARRAYS FOR EFFICIENT POINT CLOUD PROCESSING
Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model
END-TO-END MULTILINGUAL AUTOMATIC SPEECH RECOGNITION FOR LESS-RESOURCED LANGUAGES: THE CASE OF FOUR ETHIOPIAN LANGUAGES
SCALABLE MULTILEVEL QUANTIZATION FOR DISTRIBUTED DETECTION
Fast and Robust ADMM for Blind Super-resolution
AUDITORY FILTERBANKS BENEFIT UNIVERSAL SOUND SOURCE SEPARATION
Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning
ARTIFICIALLY SYNTHESISING DATA FOR AUDIO CLASSIFICATION AND SEGMENTATION TO IMPROVE SPEECH AND MUSIC DETECTION IN RADIO BROADCAST

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