14 citations · 33 across the 8 of their papers we have counts for
14 papers
Sparse Distillation: Speeding Up Text Classification by Using Bigger Student Models
Qinyuan Ye, Madian Khabsa, Mike Lewis +3
Distilling state-of-the-art transformer models into lightweight student models is an effective way to reduce computation cost at inference time. The student models are typically co…
Limitations of Autoregressive Models and Their Alternatives
Chu-Cheng Lin, Aaron Jaech, Xin Li +2
Standard autoregressive language models perform only polynomial-time computation to compute the probability of the next symbol. While this is attractive, it means they cannot model…
Distributed Gradient Methods for Nonconvex Optimization: Local and Global Convergence Guarantees
Brian Swenson, Soummya Kar, H. Vincent Poor +2
The article discusses distributed gradient-descent algorithms for computing local and global minima in nonconvex optimization. For local optimization, we focus on distributed stoch…
Personalized Language Model for Query Auto-Completion
Aaron Jaech, Mari Ostendorf
Query auto-completion is a search engine feature whereby the system suggests completed queries as the user types. Recently, the use of a recurrent neural network language model was…
Community Member Retrieval on Social Media using Textual Information
Aaron Jaech, Shobhit Hathi, Mari Ostendorf
This paper addresses the problem of community membership detection using only text features in a scenario where a small number of positive labeled examples defines the community. T…
Real-Time Prediction of the Duration of Distribution System Outages
Aaron Jaech, Baosen Zhang, Mari Ostendorf +1
This paper addresses the problem of predicting duration of unplanned power outages, using historical outage records to train a series of neural network predictors. The initial dura…