11 citations · 11 across the 1 of their papers we have counts for
5 papers
Lossless Compression of Deep Neural Networks
Thiago Serra, Abhinav Kumar, Srikumar Ramalingam
Deep neural networks have been successful in many predictive modeling tasks, such as image and language recognition, where large neural networks are often used to obtain good accur…
Template-based Minor Embedding for Adiabatic Quantum Optimization
Thiago Serra, Teng Huang, Arvind Raghunathan +1
Quantum Annealing (QA) can be used to quickly obtain near-optimal solutions for Quadratic Unconstrained Binary Optimization (QUBO) problems. In QA hardware, each decision variable…
Equivalent and Approximate Transformations of Deep Neural Networks
Abhinav Kumar, Thiago Serra, Srikumar Ramalingam
Two networks are equivalent if they produce the same output for any given input. In this paper, we study the possibility of transforming a deep neural network to another network wi…
Empirical Bounds on Linear Regions of Deep Rectifier Networks
Thiago Serra, Srikumar Ramalingam
We can compare the expressiveness of neural networks that use rectified linear units (ReLUs) by the number of linear regions, which reflect the number of pieces of the piecewise li…
How Could Polyhedral Theory Harness Deep Learning?
Thiago Serra, Christian Tjandraatmadja, Srikumar Ramalingam
The holy grail of deep learning is to come up with an automatic method to design optimal architectures for different applications. In other words, how can we effectively dimension…