Ga Wu - RankMe

43 papers A* 13A 4B 1Journal 22Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Data-centric Prediction Explanation via Kernelized Stein Discrepancy. ICLR Mahtab Sarvmaili, Hassan Sajjad, Ga Wu
2025	A*	`conf`	Resolving Lexical Bias in Model Editing. ICML Hammad Rizwan, Domenic Rosati, Ga Wu, Hassan Sajjad
2025	A*	`conf`	Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality. SIGIR Naihe Feng, Yi Sui, Shiyi Hou, Jesse C. Cresswell, Ga Wu
2025	J	`jnl`	Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality. CoRR Naihe Feng, Yi Sui, Shiyi Hou, Jesse C. Cresswell, Ga Wu
2025	J	`jnl`	Self-Supervised Representation Learning as Mutual Information Maximization. CoRR Akhlaqur Rahman Sabby, Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu
2024	J	`jnl`	Data-centric Prediction Explanation via Kernelized Stein Discrepancy. CoRR Mahtab Sarvmaili, Hassan Sajjad, Ga Wu
2024	J	`jnl`	Resolving Lexical Bias in Edit Scoping with Projector Editor Networks. CoRR Hammad Rizwan, Domenic Rosati, Ga Wu, Hassan Sajjad
2024	A*	`conf`	Self-supervised Representation Learning from Random Data Projectors. ICLR Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs
2024	J	`jnl`	Towards Understanding Human Emotional Fluctuations with Sparse Check-In Data. CoRR Sagar Paresh Shah, Ga Wu, Sean W. Kortschot, Samuel Daviau
2024	J	`jnl`	Towards Understanding the Feasibility of Machine Unlearning. CoRR Mahtab Sarvmaili, Hassan Sajjad, Ga Wu
2024	J	`jnl`	Within-basket Recommendation via Neural Pattern Associator. CoRR Kai Luo, Tianshu Shen, Lan Yao, Ga Wu, Aaron Liblong, István Fehérvári, Ruijian An, Jawad Ahmed, Harshit Mishra, Charu Pujari
2023	J	`jnl`	A User-Centric Analysis of Social Media for Stock Market Prediction. ACM Trans. Web Mohamed Reda Bouadjenek, Scott Sanner, Ga Wu
2023	B	`conf`	Large-scale User Preference Tracking via Asynchronous and Asymmetric Updating at Twitter. IEEE Big Data Ga Wu, Shivam Khare, Li Zhou, Yael Brumer, Jun-Ping Ng, Ruowei Wang
2023	J	`jnl`	Self-supervised Representation Learning From Random Data Projectors. CoRR Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs
2022	J	`jnl`	Arbitrary conditional inference in variational autoencoders via fast prior network training. Mach. Learn. Ga Wu, Justin Domke, Scott Sanner
2022	A*	`conf`	Distributional Contrastive Embedding for Clarification-based Conversational Critiquing. WWW Tianshu Shen, Zheda Mai, Ga Wu, Scott Sanner
2022	A*	`conf`	PUMA: Performance Unchanged Model Augmentation for Training Data Removal. AAAI Ga Wu, Masoud Hashemi, Christopher Srinivasa
2022	J	`jnl`	PUMA: Performance Unchanged Model Augmentation for Training Data Removal. CoRR Ga Wu, Masoud Hashemi, Christopher Srinivasa
2022	J	`jnl`	Scalable Whitebox Attacks on Tree-based Models. CoRR Giuseppe Castiglione, Gavin Ding, Masoud Hashemi, Christopher Srinivasa, Ga Wu
2022	J	`jnl`	fAux: Testing Individual Fairness via Gradient Alignment. CoRR Giuseppe Castiglione, Ga Wu, Christopher Srinivasa, Simon Prince
2021	A	`conf`	Bayesian Preference Elicitation with Keyphrase-Item Coembeddings for Interactive Recommendation. UMAP Hojin Yang, Scott Sanner, Ga Wu, Jin Peng Zhou
2021	J	`jnl`	Multi-axis Attentive Prediction for Sparse EventData: An Application to Crime Prediction. CoRR Yi Sui, Ga Wu, Scott Sanner
2021	A*	`conf`	Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models. NeurIPS Yi Sui, Ga Wu, Scott Sanner
2020	A	`conf`	A Ranking Optimization Approach to Latent Linear Critiquing for Conversational Recommender Systems. RecSys Hanze Li, Scott Sanner, Kai Luo, Ga Wu
2020	—	`conf`	Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. ICDM (Workshops) Zheda Mai, Ga Wu, Kai Luo, Scott Sanner
2020	J	`jnl`	Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. CoRR Zheda Mai, Ga Wu, Kai Luo, Scott Sanner
2020	A*	`conf`	Deep Critiquing for VAE-based Recommender Systems. SIGIR Kai Luo, Hojin Yang, Ga Wu, Scott Sanner
2020	A*	`conf`	Latent Linear Critiquing for Conversational Recommender Systems. WWW Kai Luo, Scott Sanner, Ga Wu, Hanze Li, Hojin Yang
2020	J	`jnl`	Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering. CoRR Jin Peng Zhou, Ga Wu, Zheda Mai, Scott Sanner
2020	J	`jnl`	Scalable Planning with Deep Neural Network Learned Transition Models. J. Artif. Intell. Res. Ga Wu, Buser Say, Scott Sanner
2019	A	`conf`	A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification. SDM Yakun Wang, Ga Wu, Mohamed Reda Bouadjenek, Scott Sanner, Sen Su, Zhongbao Zhang
2019	A	`conf`	Deep language-based critiquing for recommender systems. RecSys Ga Wu, Kai Luo, Scott Sanner, Harold Soh
2019	A*	`conf`	Noise Contrastive Estimation for One-Class Collaborative Filtering. SIGIR Ga Wu, Maksims Volkovs, Chee Loong Soon, Scott Sanner, Himanshu Rai
2019	A*	`conf`	One-Class Collaborative Filtering with the Queryable Variational Autoencoder. SIGIR Ga Wu, Mohamed Reda Bouadjenek, Scott Sanner
2019	J	`jnl`	Scalable Nonlinear Planning with Deep Neural Network Learned Transition Models. CoRR Ga Wu, Buser Say, Scott Sanner
2018	J	`jnl`	Aesthetic Features for Personalized Photo Recommendation. CoRR Yu Qing Zhou, Ga Wu, Scott Sanner, Putra Manggala
2018	J	`jnl`	Conditional Inference in Pre-trained Variational Autoencoders via Cross-coding. CoRR Ga Wu, Justin Domke, Scott Sanner
2018	J	`jnl`	Noise Contrastive Estimation for Scalable Linear Models for One-Class Collaborative Filtering. CoRR Ga Wu, Maksims Volkovs, Chee Loong Soon, Scott Sanner, Himanshu Rai
2018	—	`conf`	Two-stage Model for Automatic Playlist Continuation at Scale. RecSys Challenge Maksims Volkovs, Himanshu Rai, Zhaoyue Cheng, Ga Wu, Yichao Lu, Scott Sanner
2017	A*	`conf`	Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming. IJCAI Buser Say, Ga Wu, Yu Qing Zhou, Scott Sanner
2017	—	`conf`	Scalable Planning with Tensorflow for Hybrid Nonlinear Domains. NIPS Ga Wu, Buser Say, Scott Sanner
2017	J	`jnl`	Scalable Planning with Tensorflow for Hybrid Nonlinear Domains. CoRR Ga Wu, Buser Say, Scott Sanner
2015	A*	`conf`	Bayesian Model Averaging Naive Bayes (BMA-NB): Averaging over an Exponential Number of Feature Models in Linear Time. AAAI Ga Wu, Scott Sanner, Rodrigo F. S. C. Oliveira