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07/13/2023
AutoHint: Automatic Prompt Optimization with Hint Generation
This paper presents AutoHint, a novel framework for automatic prompt eng...
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06/30/2023
DeepTagger: Knowledge Enhanced Named Entity Recognition for Web-Based Ads Queries
Named entity recognition (NER) is a crucial task for online advertisemen...
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12/15/2022
Efficient Long Sequence Modeling via State Space Augmented Transformer
Transformer models have achieved superior performance in various natural...
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09/12/2022
TEDL: A Two-stage Evidential Deep Learning Method for Classification Uncertainty Quantification
In this paper, we propose TEDL, a two-stage learning approach to quantif...
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10/27/2021
Masked LARk: Masked Learning, Aggregation and Reporting worKflow
Today, many web advertising data flows involve passive cross-site tracki...
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10/17/2020
Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction
It is often critical for prediction models to be robust to distributiona...
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10/15/2020
Causal Inference in the Presence of Interference in Sponsored Search Advertising
In classical causal inference, inferring cause-effect relations from dat...
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03/18/2020
Self-Supervised Contextual Bandits in Computer Vision
Contextual bandits are a common problem faced by machine learning practi...
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02/18/2020
Data Transformation Insights in Self-supervision with Clustering Tasks
Self-supervision is key to extending use of deep learning for label scar...
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09/12/2018
A Unified Batch Online Learning Framework for Click Prediction
We present a unified framework for Batch Online Learning (OL) for Click ...
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04/18/2018
Modeling and Simultaneously Removing Bias via Adversarial Neural Networks
In real world systems, the predictions of deployed Machine Learned model...
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09/16/2014
