Search Results for author: Jay Yagnik

Found 5 papers, 0 papers with code

Predicted Variables in Programming

no code implementations ICLR 2019 Victor Carbune, Thierry Coppey, Alexander Daryin, Thomas Deselaers, Nikhil Sarda, Jay Yagnik

We leverage the existing concept of variables and create a new type, a predicted variable.

SmartChoices: Hybridizing Programming and Machine Learning

no code implementations ICLR 2019 Victor Carbune, Thierry Coppey, Alexander Daryin, Thomas Deselaers, Nikhil Sarda, Jay Yagnik

As opposed to previous work applying ML to algorithmic problems, our proposed approach does not require to drop existing implementations but seamlessly integrates into the standard software development workflow and gives full control to the software developer over how ML methods are applied.

BIG-bench Machine Learning

Deep Networks With Large Output Spaces

no code implementations23 Dec 2014 Sudheendra Vijayanarasimhan, Jonathon Shlens, Rajat Monga, Jay Yagnik

Deep neural networks have been extremely successful at various image, speech, video recognition tasks because of their ability to model deep structures within the data.

Video Recognition

Fast, Accurate Detection of 100,000 Object Classes on a Single Machine

no code implementations CVPR 2013 Thomas Dean, Mark A. Ruzon, Mark Segal, Jonathon Shlens, Sudheendra Vijayanarasimhan, Jay Yagnik

Many object detection systems are constrained by the time required to convolve a target image with a bank of filters that code for different aspects of an object's appearance, such as the presence of component parts.

object-detection Object Detection

Discriminative Segment Annotation in Weakly Labeled Video

no code implementations CVPR 2013 Kevin Tang, Rahul Sukthankar, Jay Yagnik, Li Fei-Fei

Second, we ensure that CRANE is robust to label noise, both in terms of tagged videos that fail to contain the concept as well as occasional negative videos that do.

Cannot find the paper you are looking for? You can Submit a new open access paper.