Search Results for author: Vamsi K. Ithapu

Found 14 papers, 2 papers with code

Continual self-training with bootstrapped remixing for speech enhancement

1 code implementation19 Oct 2021 Efthymios Tzinis, Yossi Adi, Vamsi K. Ithapu, Buye Xu, Anurag Kumar

Specifically, a separation teacher model is pre-trained on an out-of-domain dataset and is used to infer estimated target signals for a batch of in-domain mixtures.

Speech Enhancement Unsupervised Domain Adaptation

DPLM: A Deep Perceptual Spatial-Audio Localization Metric

no code implementations29 May 2021 Pranay Manocha, Anurag Kumar, Buye Xu, Anjali Menon, Israel D. Gebru, Vamsi K. Ithapu, Paul Calamia

Subjective evaluations are critical for assessing the perceptual realism of sounds in audio-synthesis driven technologies like augmented and virtual reality.

Audio Synthesis

Accelerating Permutation Testing in Voxel-wise Analysis through Subspace Tracking: A new plugin for SnPM

no code implementations4 Mar 2017 Felipe Gutierrez-Barragan, Vamsi K. Ithapu, Chris Hinrichs, Camille Maumet, Sterling C. Johnson, Thomas E. Nichols, Vikas Singh, the ADNI

We find that RapidPT achieves its best runtime performance on medium sized datasets ($50 \leq n \leq 200$), with speedups of 1. 5x - 38x (vs. SnPM13) and 20x-1000x (vs. NaivePT).

Low-Rank Matrix Completion

On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation

no code implementations28 Feb 2017 Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh

We seek to analyze whether network architecture and input data statistics may guide the choices of learning parameters and vice versa.


A Projection Free Method for Generalized Eigenvalue Problem With a Nonsmooth Regularizer

no code implementations ICCV 2015 Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh

Eigenvalue problems are ubiquitous in computer vision, covering a very broad spectrum of applications ranging from estimation problems in multi-view geometry to image segmentation.

Image Segmentation Semantic Segmentation +1

An NMF Perspective on Binary Hashing

no code implementations ICCV 2015 Lopamudra Mukherjee, Sathya N. Ravi, Vamsi K. Ithapu, Tyler Holmes, Vikas Singh

In this paper, we first derive an Augmented Lagrangian approach to optimize the standard binary Hashing objective (i. e., maintain fidelity with a given distance matrix).

Quantization Retrieval

On the interplay of network structure and gradient convergence in deep learning

no code implementations17 Nov 2015 Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh

The regularization and output consistency behavior of dropout and layer-wise pretraining for learning deep networks have been fairly well studied.


Convergence rates for pretraining and dropout: Guiding learning parameters using network structure

no code implementations10 Jun 2015 Vamsi K. Ithapu, Sathya Ravi, Vikas Singh

Unsupervised pretraining and dropout have been well studied, especially with respect to regularization and output consistency.


Speeding up Permutation Testing in Neuroimaging

no code implementations NeurIPS 2013 Chris Hinrichs, Vamsi K. Ithapu, Qinyuan Sun, Sterling C. Johnson, Vikas Singh

In this paper, we show that permutation testing in fact amounts to populating the columns of a very large matrix ${\bf P}$.

Matrix Completion Two-sample testing

Convergence of gradient based pre-training in Denoising autoencoders

no code implementations12 Feb 2015 Vamsi K. Ithapu, Sathya Ravi, Vikas Singh

The success of deep architectures is at least in part attributed to the layer-by-layer unsupervised pre-training that initializes the network.

Denoising Unsupervised Pre-training

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