Sharad Vikram

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We present a character-level recurrent neural network that generates relevant and coherent text given auxiliary information such as a sentiment or topic.1 Using a simple input replication strategy, we preserve the signal of auxiliary input across wider sequence intervals than can feasibly be trained by back-propagation through time. Our main results center(More)
Clustering is a powerful tool in data analysis, but it is often difficult to find a grouping that aligns with a user’s needs. To address this, several methods incorporate constraints obtained from users into clustering algorithms, but unfortunately do not apply to hierarchical clustering. We design an interactive Bayesian algorithm that incorporates user(More)
Iris recognition is the widely used biometric analysis system which is used to precisely identify any individual by measuring the iris part of the eye. But in some circumstances iris image can't be captured completely which becomes unfit to perform some analysis and direct manipulations. Other aspects such as procurement process of iris data also come into(More)
Recent technologies in vision sensors are capable of capturing 3D finger positions and movements. We propose a novel way to control and interact with computers by moving fingers in the air. The positions of fingers are precisely captured by a computer vision device. By tracking the moving patterns of fingers, we can then recognize users' intended control(More)
The advent of cost-effective DNA sequencing has provided clinics with high-resolution information about patient’s genetic variants, which has resulted in the need for efficient interpretation of this genomic data. Traditionally, variant interpretation has been dominated by many manual, time-consuming processes due to the disparate forms of relevant(More)
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