Papers
From Boltzmann Machines to Neural Networks and Back Again
Surbhi Goel, Adam Klivans, Frederic Koehler
The Power of Comparisons for Actively Learning Linear Classifiers
Max Hopkins, Daniel Kane, Shachar Lovett
Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention
Ekta Sood, Simon Tannert, Philipp Mueller et al.
Generative 3D Part Assembly via Dynamic Graph Learning
jialei huang, Guanqi Zhan, Qingnan Fan et al.
Proximity Operator of the Matrix Perspective Function and its Applications
Joong-Ho (Johann) Won
Multi-task Causal Learning with Gaussian Processes
Virginia Aglietti, Theodoros Damoulas, Mauricio Álvarez et al.
Minibatch vs Local SGD for Heterogeneous Distributed Learning
Blake E Woodworth, Kumar Kshitij Patel, Nati Srebro
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo
Yueming LYU, Yuan Yuan, Ivor W. Tsang
Unsupervised Data Augmentation for Consistency Training
Qizhe Xie, Zihang Dai, Eduard Hovy et al.
Learning Kernel Tests Without Data Splitting
Jonas Kübler, Wittawat Jitkrittum, Bernhard Schölkopf et al.
Demixed shared component analysis of neural population data from multiple brain areas
Yu Takagi, Steven Kennerley, Jun-ichiro Hirayama et al.
Boundary thickness and robustness in learning models
Yaoqing Yang, Rajiv Khanna, Yaodong Yu et al.
On 1/n neural representation and robustness
Josue Nassar, Piotr Sokol, Sueyeon Chung et al.
Multi-task Batch Reinforcement Learning with Metric Learning
Jiachen Li, Quan Vuong, Shuang Liu et al.
Wavelet Flow: Fast Training of High Resolution Normalizing Flows
Jason J. Yu, Konstantinos G. Derpanis, Marcus A Brubaker
Neurosymbolic Reinforcement Learning with Formally Verified Exploration
Greg Anderson, Abhinav Verma, Isil Dillig et al.
Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron Yield
John Choi, Krishan Kumar, Mohammad Khazali et al.
How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions
Michael Tsang, Sirisha Rambhatla, Yan Liu
Predicting Training Time Without Training
Luca Zancato, Alessandro Achille, Avinash Ravichandran et al.
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension
Ruosong Wang, Ruslan Salakhutdinov, Lin Yang
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers
Kiwon Um, Robert Brand, Yun (Raymond) Fei et al.
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence
Thomas Sutter, Imant Daunhawer, Julia Vogt
Continuous Object Representation Networks: Novel View Synthesis without Target View Supervision
Nicolai Hani, Selim Engin, Jun-Jee Chao et al.
Sparse Symplectically Integrated Neural Networks
Daniel DiPietro, Shiying Xiong, Bo Zhu
Estimating decision tree learnability with polylogarithmic sample complexity
Guy Blanc, Neha Gupta, Jane Lange et al.