Search Results for author: Charles Elkan

Found 12 papers, 2 papers with code

What we need to learn if we want to do and not just talk

no code implementations NAACL 2018 Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan

In task-oriented dialog, agents need to generate both fluent natural language responses and correct external actions like database queries and updates.

Chatbot Machine Translation

Achieving Fluency and Coherency in Task-oriented Dialog

no code implementations11 Apr 2018 Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan

We show how to combine nearest neighbor and Seq2Seq methods in a hybrid model, where nearest neighbor is used to generate fluent responses and Seq2Seq type models ensure dialog coherency and generate accurate external actions.

End-to-End Offline Goal-Oriented Dialog Policy Learning via Policy Gradient

no code implementations7 Dec 2017 Li Zhou, Kevin Small, Oleg Rokhlenko, Charles Elkan

Learning a goal-oriented dialog policy is generally performed offline with supervised learning algorithms or online with reinforcement learning (RL).

Goal-Oriented Dialog Offline RL +1

Visualizing the Consequences of Evidence in Bayesian Networks

no code implementations4 Jul 2017 Clifford Champion, Charles Elkan

This paper addresses the challenge of viewing and navigating Bayesian networks as their structural size and complexity grow.

Predicting Surgery Duration with Neural Heteroscedastic Regression

no code implementations17 Feb 2017 Nathan Ng, Rodney A Gabriel, Julian McAuley, Charles Elkan, Zachary C. Lipton

Scheduling surgeries is a challenging task due to the fundamental uncertainty of the clinical environment, as well as the risks and costs associated with under- and over-booking.

Learning to Diagnose with LSTM Recurrent Neural Networks

no code implementations11 Nov 2015 Zachary C. Lipton, David C. Kale, Charles Elkan, Randall Wetzel

We present the first study to empirically evaluate the ability of LSTMs to recognize patterns in multivariate time series of clinical measurements.

Time Series

A Critical Review of Recurrent Neural Networks for Sequence Learning

2 code implementations29 May 2015 Zachary C. Lipton, John Berkowitz, Charles Elkan

Recurrent neural networks (RNNs) are connectionist models that capture the dynamics of sequences via cycles in the network of nodes.

Handwriting Recognition Image Captioning +5

Efficient Elastic Net Regularization for Sparse Linear Models

no code implementations24 May 2015 Zachary C. Lipton, Charles Elkan

This paper provides closed-form updates for the popular squared norm $\ell^2_2$ and elastic net regularizers.

Differential Privacy and Machine Learning: a Survey and Review

no code implementations24 Dec 2014 Zhanglong Ji, Zachary C. Lipton, Charles Elkan

The objective of machine learning is to extract useful information from data, while privacy is preserved by concealing information.

Thresholding Classifiers to Maximize F1 Score

1 code implementation8 Feb 2014 Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy

As another special case, if the classifier is completely uninformative, then the optimal behavior is to classify all examples as positive.

Classification Decision Making +1

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