2 citations · 4 across the 6 of their papers we have counts for
6 papers
Multimodal RAG for Unstructured Data:Leveraging Modality-Aware Knowledge Graphs with Hybrid Retrieval
Rashmi R, Vidyadhar Upadhya
Current Retrieval-Augmented Generation (RAG) systems primarily operate on unimodal textual data, limiting their effectiveness on unstructured multimodal documents. Such documents o…
Learning Gaussian-Bernoulli RBMs using Difference of Convex Functions Optimization
Vidyadhar Upadhya, P S Sastry
The Gaussian-Bernoulli restricted Boltzmann machine (GB-RBM) is a useful generative model that captures meaningful features from the given -dimensional continuous data. The diff…
Efficient Learning of Restricted Boltzmann Machines Using Covariance Estimates
Vidyadhar Upadhya, P. S. Sastry
Learning RBMs using standard algorithms such as CD(k) involves gradient descent on the negative log-likelihood. One of the terms in the gradient, which involves expectation w.r.t.…
Learning RBM with a DC programming Approach
Vidyadhar Upadhya, P. S. Sastry
By exploiting the property that the RBM log-likelihood function is the difference of convex functions, we formulate a stochastic variant of the difference of convex functions (DC)…
Empirical Analysis of Sampling Based Estimators for Evaluating RBMs
Vidyadhar Upadhya, P. S. Sastry
The Restricted Boltzmann Machines (RBM) can be used either as classifiers or as generative models. The quality of the generative RBM is measured through the average log-likelihood…
Blind Non-parametric Statistics for Multichannel Detection Based on Statistical Covariances
Vidyadhar Upadhya, Devendra Jalihal
We consider the problem of detecting the presence of a spatially correlated multichannel signal corrupted by additive Gaussian noise (i.i.d across sensors). No prior knowledge is a…