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05/31/2023
IDAS: Intent Discovery with Abstractive Summarization
Intent discovery is the task of inferring latent intents from a set of u...
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02/27/2023
Linear pretraining in recurrent mixture density networks
We present a method for pretraining a recurrent mixture density network ...
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10/21/2022
Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals
For text classification tasks, finetuned language models perform remarka...
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09/28/2021
Risk averse non-stationary multi-armed bandits
This paper tackles the risk averse multi-armed bandits problem when incu...
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04/08/2021
A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders
Powerful sentence encoders trained for multiple languages are on the ris...
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03/08/2021
Bias-Corrected Peaks-Over-Threshold Estimation of the CVaR
The conditional value-at-risk (CVaR) is a useful risk measure in fields ...
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12/03/2019
Risk-Averse Action Selection Using Extreme Value Theory Estimates of the CVaR
The Conditional Value-at-Risk (CVaR) is a useful risk measure in machine...
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02/26/2019
Using Ternary Rewards to Reason over Knowledge Graphs with Deep Reinforcement Learning
In this paper, we investigate the practical challenges of using reinforc...
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08/28/2018
Explaining Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules?
Character-level features are currently used in different neural network-...
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08/27/2018
Predefined Sparseness in Recurrent Sequence Models
Inducing sparseness while training neural networks has been shown to yie...
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07/25/2017
Dual Rectified Linear Units (DReLUs): A Replacement for Tanh Activation Functions in Quasi-Recurrent Neural Networks
In this paper, we introduce a novel type of Rectified Linear Unit (ReLU)...
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07/19/2017