activity
20142019
most citedDeep Learning Aided Rational Design of Oxide Glasses

5 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.mtrl-sci20195 cited

Deep Learning Aided Rational Design of Oxide Glasses

R. Ravinder, Karthikeya H. Sreedhara, Suresh Bishnoi +5

Despite the extensive usage of oxide glasses for a few millennia, the composition-property relationships in these materials still remain poorly understood. While empirical and phys…

cs.LG2019

Effect of Various Regularizers on Model Complexities of Neural Networks in Presence of Input Noise

Mayank Sharma, Aayush Yadav, Sumit Soman +1

Deep neural networks are over-parameterized, which implies that the number of parameters are much larger than the number of samples used to train the network. Even in such a regime…

cs.CV20162 cited

Examining Representational Similarity in ConvNets and the Primate Visual Cortex

Abhimanyu Dubey, Jayadeva, Sumeet Agarwal

We compare several ConvNets with different depth and regularization techniques with multi-unit macaque IT cortex recordings and assess the impact of the same on representational si…

cs.LG20153 cited

Learning a Fuzzy Hyperplane Fat Margin Classifier with Minimum VC dimension

Jayadeva, Sanjit Singh Batra, Siddarth Sabharwal

The Vapnik-Chervonenkis (VC) dimension measures the complexity of a learning machine, and a low VC dimension leads to good generalization. The recently proposed Minimal Complexity…

cs.LG20144 cited

Feature Selection through Minimization of the VC dimension

Jayadeva, Sanjit S. Batra, Siddharth Sabharwal

Feature selection involes identifying the most relevant subset of input features, with a view to improving generalization of predictive models by reducing overfitting. Directly sea…

math.DS2014

Convergence results for continuous-time dynamics arising in ant colony optimization

Pierre-Alexandre Bliman, Amit Bhaya, Eugenius Kaszkurewicz +1

This paper studies the asymptotic behavior of several continuous-time dynamical systems which are analogs of ant colony optimization algorithms that solve shortest path problems. L…