Search Results for author:
Found 8 papers, 6 papers with code
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
In this paper, we show that a Bernoulli sampling attention mechanism based on Locality Sensitive Hashing (LSH), decreases the quadratic complexity of such models to linear.
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention
The scalability of Nystr\"{o}mformer enables application to longer sequences with thousands of tokens.
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MobileDets: Searching for Object Detection Architectures for Mobile Accelerators
By incorporating regular convolutions in the search space and directly optimizing the network architectures for object detection, we obtain a family of object detection models, MobileDets, that achieve state-of-the-art results across mobile accelerators.
Mixed Effects Neural Networks (MeNets) With Applications to Gaze Estimation
nature of this data suggests better estimation may be possible if the model explicitly made use of such "repeated measurements" from each user as is commonly done in classical statistical analysis using so-called mixed effects models.
Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?
In the latter case, the optimization is often non-differentiable and also not very amenable to derivative-free optimization methods.
ANTNets: Mobile Convolutional Neural Networks for Resource Efficient Image Classification
It boosts the representational power by modeling, in a high dimensional space, interdependency of channels between a depthwise convolution layer and a projection layer in the ANTBlocks.
Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty
We provide simple schemes to build Bayesian Neural Networks (BNNs), block by block, inspired by a recent idea of computation skeletons.
Filter Flow Made Practical: Massively Parallel and Lock-Free
This paper is inspired by a relatively recent work of Seitz and Baker which introduced the so-called Filter Flow model.
