Papers
Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing
Hao Zhou, Shaoming Li, Guibin Jiang et al.
Discriminability and Transferability Estimation: A Bayesian Source Importance Estimation Approach for Multi-Source-Free Domain Adaptation
Zhongyi Han, Zhiyan Zhang, Fan Wang et al.
Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from a Conditional Causal Perspective
Jiangmeng Li, Yanan Zhang, Wenwen Qiang et al.
Disentangled CVAEs with Contrastive Learning for Explainable Recommendation
Linlin Wang, Zefeng Cai, Gerard de Melo et al.
Disentangled Representation for Causal Mediation Analysis
Ziqi Xu, Debo Cheng, Jiuyong Li et al.
Disentangling Reafferent Effects by Doing Nothing
Benedict Wilkins, Kostas Stathis
Disentangling the Benefits of Self-Supervised Learning to Deployment-Driven Downstream Tasks of Satellite Images (Student Abstract)
Zhuo Deng, Yibing Wei, Mingye Zhu et al.
DisGUIDE: Disagreement-Guided Data-Free Model Extraction
Jonathan Rosenthal, Eric Enouen, Hung Viet Pham et al.
Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting
Wei Fan, Pengyang Wang, Dongkun Wang et al.
DISPUTool 2.0: A Modular Architecture for Multi-Layer Argumentative Analysis of Political Debates
Pierpaolo Goffredo, Elena Cabrio, Serena Villata et al.
Distantly-Supervised Named Entity Recognition with Adaptive Teacher Learning and Fine-Grained Student Ensemble
Xiaoye Qu, Jun Zeng, Daizong Liu et al.
Distributed Projection-Free Online Learning for Smooth and Convex Losses
Yibo Wang, Yuanyu Wan, Shimao Zhang et al.
Distributed Spectrum-Based Fault Localization
Avraham Natan, Roni Stern, Meir Kalech
Distributionally Robust Optimization with Probabilistic Group
Soumya Suvra Ghosal, Yixuan Li
Diversified and Realistic 3D Augmentation via Iterative Construction, Random Placement, and HPR Occlusion
Jungwook Shin, Jaeill Kim, Kyungeun Lee et al.
Diversity Maximization in the Presence of Outliers
Daichi Amagata
DM²: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching
Caroline Wang, Ishan Durugkar, Elad Liebman et al.
DMIS: Dynamic Mesh-Based Importance Sampling for Training Physics-Informed Neural Networks
Zijiang Yang, Zhongwei Qiu, Dongmei Fu
DNG: Taxonomy Expansion by Exploring the Intrinsic Directed Structure on Non-gaussian Space
Songlin Zhai, Weiqing Wang, Yuanfang Li et al.
DocEdit: Language-Guided Document Editing
Puneet Mathur, Rajiv Jain, Jiuxiang Gu et al.
Does It Pay to Optimize AUC?
Baojian Zhou, Steven Skiena
Does Knowing When Help Is Needed Improve Subgoal Hint Performance in an Intelligent Data-Driven Logic Tutor?
Nazia Alam, Mehak Maniktala, Behrooz Mostafavi et al.
Do Invariances in Deep Neural Networks Align with Human Perception?
Vedant Nanda, Ayan Majumdar, Camila Kolling et al.
Domain Adaptation with Adversarial Training on Penultimate Activations
Tao Sun, Cheng Lu, Haibin Ling