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Found 6 papers, 0 papers with code
Intent Discovery for Enterprise Virtual Assistants: Applications of Utterance Embedding and Clustering to Intent Mining
A key challenge in the creation and refinement of virtual assistants is the ability to mine unlabeled utterance data to discover common intents.
Lightweight Transformers for Conversational AI
To understand how training on conversational language impacts performance of pre-trained models on downstream dialogue tasks, we build compact Transformer-based Language Models from scratch on several large corpora of conversational data.
A Hybrid Approach to Scalable and Robust Spoken Language Understanding in Enterprise Virtual Agents
Spoken language understanding (SLU) extracts the intended mean- ing from a user utterance and is a critical component of conversational virtual agents.
Deep Clustering with Measure Propagation
For example, deep embedded clustering (DEC) has greatly improved the unsupervised clustering performance, by using stacked autoencoders for representation learning.
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Deep Clustering
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Compressive Sensing of Signals from a GMM with Sparse Precision Matrices
This paper is concerned with compressive sensing of signals drawn from a Gaussian mixture model (GMM) with sparse precision matrices.
Faithful Variable Screening for High-Dimensional Convex Regression
We study the problem of variable selection in convex nonparametric regression.
