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Model Teachers: Startups Make Schools Smarter With Machine Learning

Like two valedictorians, SimInsights and Photomath tell stories worth hearing about how AI is advancing education. SimInsights in Irvine, Calif.,…

3 years ago

Improving Voice Trigger Detection with Metric Learning

Voice trigger detection is an important task, which enables activating a voice assistant when a target user speaks a keyword…

3 years ago

NeILF: Neural Incident Light Field for Material and Lighting Estimation

We present a differentiable rendering framework for material and lighting estimation from multi-view images and a reconstructed geometry. In the…

3 years ago

Integrating Categorical Features in End-To-End ASR

All-neural, end-to-end ASR systems gained rapid interest from the speech recognition community. Such systems convert speech input to text units…

3 years ago

Combining Compressions for Multiplicative Size Scaling on Natural Language Tasks

Quantization, knowledge distillation, and magnitude pruning are among the most popular methods for neural network compression in NLP. Independently, these…

3 years ago

CVNets: High Performance Library for Computer Vision

We introduce CVNets, a high-performance open-source library for training deep neural networks for visual recognition tasks, including classification, detection, and…

3 years ago

Space-Efficient Representation of Entity-centric Query Language Models

Virtual assistants make use of automatic speech recognition (ASR) to help users answer entity-centric queries. However, spoken entity recognition is…

3 years ago

FORML: Learning to Reweight Data for Fairness

Machine learning models are trained to minimize the mean loss for a single metric, and thus typically do not consider…

3 years ago

A Dense Material Segmentation Dataset for Indoor and Outdoor Scene Parsing

A key algorithm for understanding the world is material segmentation, which assigns a(metal, glass, etc.) to each pixel.…

3 years ago

Regularized Training of Nearest Neighbor Language Models

Including memory banks in a natural language processing architecture increases model capacity by equipping it with additional data at inference…

3 years ago