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01/27/2023
EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval
Large neural models (such as Transformers) achieve state-of-the-art perf...
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10/31/2022
Learning to Navigate Wikipedia by Taking Random Walks
A fundamental ability of an intelligent web-based agent is seeking out a...
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01/29/2022
A Context-Integrated Transformer-Based Neural Network for Auction Design
One of the central problems in auction design is developing an incentive...
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06/10/2021
Thompson Sampling with a Mixture Prior
We study Thompson sampling (TS) in online decision-making problems where...
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02/11/2021
Meta-Thompson Sampling
Efficient exploration in multi-armed bandits is a fundamental online lea...
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10/22/2020
Scalable Bottom-Up Hierarchical Clustering
Bottom-up algorithms such as the classic hierarchical agglomerative clus...
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09/08/2020
Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function
In this paper, we study bidirectional LSTM network for the task of text ...
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07/28/2020
Big Bird: Transformers for Longer Sequences
Transformers-based models, such as BERT, have been one of the most succe...
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06/21/2019
Randomized Exploration in Generalized Linear Bandits
We study two randomized algorithms for generalized linear bandits, GLM-T...
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12/14/2018
On the Convergence of Federated Optimization in Heterogeneous Networks
The burgeoning field of federated learning involves training machine lea...
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01/19/2018
Investigating the Working of Text Classifiers
Text classification is one of the most widely studied task in natural la...
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03/10/2017
