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09/16/2023
Bridging Dense and Sparse Maximum Inner Product Search
Maximum inner product search (MIPS) over dense and sparse vectors have p...
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06/21/2023
Post-hoc Selection of Pareto-Optimal Solutions in Search and Recommendation
Information Retrieval (IR) and Recommender Systems (RS) tasks are moving...
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06/15/2023
Neural Network Compression using Binarization and Few Full-Precision Weights
Quantization and pruning are known to be two effective Deep Neural Netwo...
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05/15/2023
Efficient and Effective Tree-based and Neural Learning to Rank
This monograph takes a step towards promoting the study of efficiency in...
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01/25/2023
An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors
Maximum Inner Product Search or top-k retrieval on sparse vectors is wel...
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11/25/2022
Caching Historical Embeddings in Conversational Search
Rapid response, namely low latency, is fundamental in search application...
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06/01/2022
ILMART: Interpretable Ranking with Constrained LambdaMART
Interpretable Learning to Rank (LtR) is an emerging field within the res...
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11/26/2021
An Optimal Algorithm for Finding Champions in Tournament Graphs
A tournament graph T = (V, E ) is an oriented complete graph, which can ...
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05/06/2021
Learning Early Exit Strategies for Additive Ranking Ensembles
Modern search engine ranking pipelines are commonly based on large machi...
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11/17/2020
Dynamic Hard Pruning of Neural Networks at the Edge of the Internet
Neural Networks (NN), although successfully applied to several Artificia...
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04/30/2020
Query-level Early Exit for Additive Learning-to-Rank Ensembles
Search engine ranking pipelines are commonly based on large ensembles of...
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04/29/2020
Training Curricula for Open Domain Answer Re-Ranking
In precision-oriented tasks like answer ranking, it is more important to...
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04/29/2020
Efficient Document Re-Ranking for Transformers by Precomputing Term Representations
Deep pretrained transformer networks are effective at various ranking ta...
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04/29/2020
