Papers
Towards Understanding and Improving GFlowNet Training
Max W Shen, Emmanuel Bengio, Ehsan Hajiramezanali et al.
Towards Understanding and Reducing Graph Structural Noise for GNNs
Mingze Dong, Yuval Kluger
Towards Understanding Ensemble Distillation in Federated Learning
Sejun Park, Kihun Hong, Ganguk Hwang
Towards Understanding Generalization of Graph Neural Networks
Huayi Tang, Yong Liu
Towards Understanding Generalization of Macro-AUC in Multi-label Learning
Guoqiang Wu, Chongxuan Li, Yilong Yin
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation
Zhaoyan Liu, Noël Vouitsis, Satya Krishna Gorti et al.
Tractable Control for Autoregressive Language Generation
Honghua Zhang, Meihua Dang, Nanyun Peng et al.
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts
Dirk Van Der Hoeven, Ciara Pike-Burke, Hao Qiu et al.
Trainability, Expressivity and Interpretability in Gated Neural ODEs
Timothy Doyeon Kim, Tankut Can, Kamesh Krishnamurthy
Training Deep Surrogate Models with Large Scale Online Learning
Lucas Thibaut Meyer, Marc Schouler, Robert Alexander Caulk et al.
Training-Free Neural Active Learning with Initialization-Robustness Guarantees
Apivich Hemachandra, Zhongxiang Dai, Jasraj Singh et al.
Training Normalizing Flows from Dependent Data
Matthias Kirchler, Christoph Lippert, Marius Kloft
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning
Brett Daley, Martha White, Christopher Amato et al.
TRAK: Attributing Model Behavior at Scale
Sung Min Park, Kristian Georgiev, Andrew Ilyas et al.
Transformed Distribution Matching for Missing Value Imputation
He Zhao, Ke Sun, Amir Dezfouli et al.
Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization
Chanyeong Kim, Jongwoong Park, Hyunglip Bae et al.
Transformers as Algorithms: Generalization and Stability in In-context Learning
Yingcong Li, Muhammed Emrullah Ildiz, Dimitris Papailiopoulos et al.
Transformers Learn In-Context by Gradient Descent
Johannes Von Oswald, Eyvind Niklasson, Ettore Randazzo et al.
Transformers Meet Directed Graphs
Simon Geisler, Yujia Li, Daniel J Mankowitz et al.
Trapdoor Normalization with Irreversible Ownership Verification
Hanwen Liu, Zhenyu Weng, Yuesheng Zhu et al.
Traversing Between Modes in Function Space for Fast Ensembling
Eunggu Yun, Hyungi Lee, Giung Nam et al.
Trompt: Towards a Better Deep Neural Network for Tabular Data
Kuan-Yu Chen, Ping-Han Chiang, Hsin-Rung Chou et al.
Truncating Trajectories in Monte Carlo Reinforcement Learning
Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli
Trustworthy Policy Learning under the Counterfactual No-Harm Criterion
Haoxuan Li, Chunyuan Zheng, Yixiao Cao et al.