Zobrazeno 1 - 10
of 478
pro vyhledávání: '"Tandon Ravi"'
Autor:
Zhong, Meiyu, Tandon, Ravi
Adversarial training is one of the predominant techniques for training classifiers that are robust to adversarial attacks. Recent work, however has found that adversarial training, which makes the overall classifier robust, it does not necessarily pr
Externí odkaz:
http://arxiv.org/abs/2411.14424
We propose a new approach for fine-grained uncertainty quantification (UQ) using a collision matrix. For a classification problem involving $K$ classes, the $K\times K$ collision matrix $S$ measures the inherent (aleatoric) difficulty in distinguishi
Externí odkaz:
http://arxiv.org/abs/2411.12127
In our previous works, we defined Local Information Privacy (LIP) as a context-aware privacy notion and presented the corresponding privacy-preserving mechanism. Then we claim that the mechanism satisfies epsilon-LIP for any epsilon>0 for arbitrary P
Externí odkaz:
http://arxiv.org/abs/2410.12309
Deep Neural Network (DNN) based classifiers have recently been used for the modulation classification of RF signals. These classifiers have shown impressive performance gains relative to conventional methods, however, they are vulnerable to impercept
Externí odkaz:
http://arxiv.org/abs/2410.06339
Autor:
Bhattacharjee, Payel, Tandon, Ravi
Causal Graph Discovery (CGD) is the process of estimating the underlying probabilistic graphical model that represents joint distribution of features of a dataset. CGD-algorithms are broadly classified into two categories: (i) Constraint-based algori
Externí odkaz:
http://arxiv.org/abs/2409.19060
Autor:
Uttarilli Anusha, Amalakanti Sridhar, Kommoju Phaneeswara-Rao, Sharma Srihari, Goyal Pankaj, Manjunath Gowrang Kasaba, Upadhayay Vineet, Parveen Alisha, Tandon Ravi, Prasad Kumar Suranjit, Dakal Tikam Chand, Ben Shlomo Izhar, Yousef Malik, Neerathilingam Muniasamy, Kumar Abhishek
Publikováno v:
Journal of Integrative Bioinformatics, Vol 18, Iss 1, Pp 27-43 (2021)
The pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected millions of people and claimed thousands of lives. Starting in China, it is arguably the most precipitous glob
Externí odkaz:
https://doaj.org/article/4b03a3ab3c614549bbbdcb43257be45d
Autor:
Zhong, Meiyu, Tandon, Ravi
Certifiable robustness gives the guarantee that small perturbations around an input to a classifier will not change the prediction. There are two approaches to provide certifiable robustness to adversarial examples: a) explicitly training classifiers
Externí odkaz:
http://arxiv.org/abs/2407.02811
Counterfactuals, or modified inputs that lead to a different outcome, are an important tool for understanding the logic used by machine learning classifiers and how to change an undesirable classification. Even if a counterfactual changes a classifie
Externí odkaz:
http://arxiv.org/abs/2405.11195
Autor:
Zhong, Meiyu, Tandon, Ravi
With the growing adoption of machine learning (ML) systems in areas like law enforcement, criminal justice, finance, hiring, and admissions, it is increasingly critical to guarantee the fairness of decisions assisted by ML. In this paper, we study th
Externí odkaz:
http://arxiv.org/abs/2405.07393
High-Level Synthesis (HLS) Design Space Exploration (DSE) is a widely accepted approach for efficiently exploring Pareto-optimal and optimal hardware solutions during the HLS process. Several HLS benchmarks and datasets are available for the research
Externí odkaz:
http://arxiv.org/abs/2404.14754