33 citations · 71 across the 6 of their papers we have counts for
6 papers
RISSOLE: Parameter-efficient Diffusion Models via Block-wise Generation and Retrieval-Guidance
Avideep Mukherjee, Soumya Banerjee, Piyush Rai +1
Diffusion-based models demonstrate impressive generation capabilities. However, they also have a massive number of parameters, resulting in enormous model sizes, thus making them u…
Robust Black-box Testing of Deep Neural Networks using Co-Domain Coverage
Aishwarya Gupta, Indranil Saha, Piyush Rai
Rigorous testing of machine learning models is necessary for trustworthy deployments. We present a novel black-box approach for generating test-suites for robust testing of deep ne…
Novel Class Discovery without Forgetting
K J Joseph, Sujoy Paul, Gaurav Aggarwal +4
Humans possess an innate ability to identify and differentiate instances that they are not familiar with, by leveraging and adapting the knowledge that they have acquired so far. I…
Earliness-Aware Deep Convolutional Networks for Early Time Series Classification
Wenlin Wang, Changyou Chen, Wenqi Wang +2
We present Earliness-Aware Deep Convolutional Networks (EA-ConvNets), an end-to-end deep learning framework, for early classification of time series data. Unlike most existing meth…
Flexible Modeling of Latent Task Structures in Multitask Learning
Alexandre Passos, Piyush Rai, Jacques Wainer +1
Multitask learning algorithms are typically designed assuming some fixed, a priori known latent structure shared by all the tasks. However, it is usually unclear what type of laten…
Streamed Learning: One-Pass SVMs
Piyush Rai, Hal Daumé, Suresh Venkatasubramanian
We present a streaming model for large-scale classification (in the context of -SVM) by leveraging connections between learning and computational geometry. The streaming mo…