Media Summary: Jiacheng Li, University of California, San Diego. Martin Pavlovski - Short promotional video for the paper ?Extreme Tianxiang Zhao, the Pennsylvania State University Imitation learning requires a large number of expert demonstrations to learn ...

Kdd 2023 Multi Factor Sequential - Detailed Analysis & Overview

Jiacheng Li, University of California, San Diego. Martin Pavlovski - Short promotional video for the paper ?Extreme Tianxiang Zhao, the Pennsylvania State University Imitation learning requires a large number of expert demonstrations to learn ... Pengfei Luo, University of Science and Technology of China In this promotional video, we provide a brief overview of the ... Zhiyuan Peng, Santa Clara University This is a brief introduction to our paper "Entity-aware of Mulit-task Learning for Query ... Yunjia Xi, Shanghai Jiao Tong University.

Lorenzo Perini, KU Leuven Nowadays, sustainable energy is becoming more and more important. Wind turbines can produce ... Runlong Yu, University of Science and Technology of China Presentation video - short version Predicting Click-Through Rates for ... Jianling Wang, Google Fresh uploads, especially those from less popular content providers, face a significant barrier to be picked ... Kunal Dahiya, IIT Delhi Large language models or encoders are widely used in real-world search and recommendation ...

Photo Gallery

KDD 2023 - Multi-factor Sequential Re-ranking with Perception-Aware Diversification
KDD 2023 - Text Is All You Need: Learning Language Representations for Sequential Recommendation
KDD 2023 - Extreme Multi-Label Classification for Ad Targeting using Factorization Machines
KDD 2023 - A Sequence-to-Sequence Approach with Mixed Pointers to Topic Segmentation
KDD 2023 - Skill Discovery for Learning from Imperfect Demonstration
KDD 2023 - Multi-Grained Multimodal Interaction Network for Entity Linking
KDD 2023 - Entity-aware of Mulit-task Learning for Query Understanding at Walmart
KDD 2023 - On-device Integrated Re-ranking with Heterogeneous Behavior Modeling
KDD 2023 - Learning from positive and unlabeled multi-instance bags in anomaly detection
KDD 2023 - Cognitive Evolutionary Search to Select Feature Interactions
KDD 2023 - How to robustly detect failures with 3 types of telemetry data?
KDD 2023 - Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation
View Detailed Profile
KDD 2023 - Multi-factor Sequential Re-ranking with Perception-Aware Diversification

KDD 2023 - Multi-factor Sequential Re-ranking with Perception-Aware Diversification

Yue Xu, Alibaba Group

KDD 2023 - Text Is All You Need: Learning Language Representations for Sequential Recommendation

KDD 2023 - Text Is All You Need: Learning Language Representations for Sequential Recommendation

Jiacheng Li, University of California, San Diego.

KDD 2023 - Extreme Multi-Label Classification for Ad Targeting using Factorization Machines

KDD 2023 - Extreme Multi-Label Classification for Ad Targeting using Factorization Machines

Martin Pavlovski - Short promotional video for the paper ?Extreme

KDD 2023 - A Sequence-to-Sequence Approach with Mixed Pointers to Topic Segmentation

KDD 2023 - A Sequence-to-Sequence Approach with Mixed Pointers to Topic Segmentation

Jinxiong Xia, Peking University.

KDD 2023 - Skill Discovery for Learning from Imperfect Demonstration

KDD 2023 - Skill Discovery for Learning from Imperfect Demonstration

Tianxiang Zhao, the Pennsylvania State University Imitation learning requires a large number of expert demonstrations to learn ...

KDD 2023 - Multi-Grained Multimodal Interaction Network for Entity Linking

KDD 2023 - Multi-Grained Multimodal Interaction Network for Entity Linking

Pengfei Luo, University of Science and Technology of China In this promotional video, we provide a brief overview of the ...

KDD 2023 - Entity-aware of Mulit-task Learning for Query Understanding at Walmart

KDD 2023 - Entity-aware of Mulit-task Learning for Query Understanding at Walmart

Zhiyuan Peng, Santa Clara University This is a brief introduction to our paper "Entity-aware of Mulit-task Learning for Query ...

KDD 2023 - On-device Integrated Re-ranking with Heterogeneous Behavior Modeling

KDD 2023 - On-device Integrated Re-ranking with Heterogeneous Behavior Modeling

Yunjia Xi, Shanghai Jiao Tong University.

KDD 2023 - Learning from positive and unlabeled multi-instance bags in anomaly detection

KDD 2023 - Learning from positive and unlabeled multi-instance bags in anomaly detection

Lorenzo Perini, KU Leuven Nowadays, sustainable energy is becoming more and more important. Wind turbines can produce ...

KDD 2023 - Cognitive Evolutionary Search to Select Feature Interactions

KDD 2023 - Cognitive Evolutionary Search to Select Feature Interactions

Runlong Yu, University of Science and Technology of China Presentation video - short version Predicting Click-Through Rates for ...

KDD 2023 - How to robustly detect failures with 3 types of telemetry data?

KDD 2023 - How to robustly detect failures with 3 types of telemetry data?

Chenyu Zhao, Nankai University.

KDD 2023 - Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation

KDD 2023 - Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation

Jianling Wang, Google Fresh uploads, especially those from less popular content providers, face a significant barrier to be picked ...

KDD 2023 - Deep Encoders with Auxiliary Parameters for Extreme Classification

KDD 2023 - Deep Encoders with Auxiliary Parameters for Extreme Classification

Kunal Dahiya, IIT Delhi Large language models or encoders are widely used in real-world search and recommendation ...