Vamsi K Ithapu — accepted AI-conference papers

2023

Learning to Personalize Equalization for High-Fidelity Spatial Audio Reproduction

Arjun Gupta, Pablo Hoffmann, Sebastian Prepelita, Philip W. Robinson, Vamsi K. Ithapu, David L. Alon

ICASSP 2023accepted

Reproducing accurate and perceptually realistic spatial audio for augmented and virtual reality (AR/VR) requires the headphones to have a flat frequency response. This can be achieved by equalizing the headphone transducers’ output given the transfer function between the transducer and the human ear…

Cited by 0 Source ↗Scholar ↗

2022

Continual Self-Training With Bootstrapped Remixing For Speech Enhancement

Efthymios Tzinis, Yossi Adi, Vamsi K. Ithapu, Buye Xu, Anurag Kumar

ICASSP 2022accepted

We propose RemixIT, a simple and novel self-supervised training method for speech enhancement. The proposed method is based on a continuously self-training scheme that overcomes limitations from previous studies including assumptions for the in-domain noise distribution and having access to clean ta…

Cited by 0 Source ↗Scholar ↗

2017

The Incremental Multiresolution Matrix Factorization Algorithm

Vamsi K. Ithapu, Risi Kondor, Sterling C. Johnson, Vikas Singh

CVPR 2017poster

Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices -- an important aspect in the success of many vision…

Cited by 14 PDF ↗Scholar ↗

2017

When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications

Hao Henry Zhou, Yilin Zhang, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh

ICML 2017poster

Many studies in biomedical and health sciences involve small sample sizes due to logistic or financial constraints. Often, identifying weak (but scientifically interesting) associations between a set of predictors and a response necessitates pooling datasets from multiple diverse labs or groups. Whi…

Cited by 18 Source ↗PDF ↗code ↗Scholar ↗

2016

Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease

Hao Zhou, Vamsi K Ithapu, Sathya Narayanan Ravi, Vikas Singh, Grace Wahba, Sterling C Johnson

NeurIPS 2016poster

Consider samples from two different data sources $\{\mathbf{x_s^i}\} \sim P_{\rm source}$ and $\{\mathbf{x_t^i}\} \sim P_{\rm target}$. We only observe their transformed versions $h(\mathbf{x_s^i})$ and $g(\mathbf{x_t^i})$, for some known function class $h(\cdot)$ and $g(\cdot)$. Our goal is to perf…

Cited by 20 Source ↗PDF ↗Scholar ↗

2015

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

Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson +1

ICCV 2015poster

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. Few other linear algebra problems have a more mature set of numerical routines available and many computer vision libra…

Cited by 13 PDF ↗Scholar ↗

2015

An NMF Perspective on Binary Hashing

Lopamudra Mukherjee, Sathya N. Ravi, Vamsi K. Ithapu, Tyler Holmes, Vikas Singh

ICCV 2015poster

The pervasiveness of massive data repositories has led to much interest in efficient methods for indexing, search, and retrieval. For image data, a rapidly developing body of work for these applications shows impressive performance with methods that broadly fall under the umbrella term of Binary Has…

Cited by 15 PDF ↗Scholar ↗