Papers
11,951 papers found
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
Zhong Li, Jiequn Han, Weinan E et al.
On the Dynamics of Training Attention Models
Haoye Lu, Yongyi Mao, Amiya Nayak
On the Feasibility of the Danish Model of Intonational Transcription: Phonetic Evidence from Jutlandic Danish
Anna Bothe Jespersen, Pavel Šturm, Míša Hejná
On the geometry of generalization and memorization in deep neural networks
Cory Stephenson, suchismita padhy, Abhinav Ganesh et al.
On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
On the Origin of Implicit Regularization in Stochastic Gradient Descent
Samuel L Smith, Benoit Dherin, David Barrett et al.
On the role of planning in model-based deep reinforcement learning
Jessica B Hamrick, Abram L. Friesen, Feryal Behbahani et al.
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Marius Mosbach, Maksym Andriushchenko, Dietrich Klakow
On the Suboptimality of Thompson Sampling in High Dimensions
Raymond Zhang, Richard Combes
On the Transfer of Disentangled Representations in Realistic Settings
Andrea Dittadi, Frederik Träuble, Francesco Locatello et al.
On the Universality of Rotation Equivariant Point Cloud Networks
Nadav Dym, Haggai Maron
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Anurag Ajay, Aviral Kumar, Pulkit Agrawal et al.
Open Question Answering over Tables and Text
Wenhu Chen, Ming-Wei Chang, Eva Schlinger et al.
Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
Shikuang Deng, Shi Gu
Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
Atsushi Nitanda, Taiji Suzuki
Optimal Regularization can Mitigate Double Descent
Preetum Nakkiran, Prayaag Venkat, Sham M. Kakade et al.
Optimism in Reinforcement Learning with Generalized Linear Function Approximation
Yining Wang, Ruosong Wang, Simon Shaolei Du et al.
Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning
Shauharda Khadka, Estelle Aflalo, Mattias Marder et al.
Orthogonalizing Convolutional Layers with the Cayley Transform
Asher Trockman, J Zico Kolter
Overfitting for Fun and Profit: Instance-Adaptive Data Compression
Ties van Rozendaal, Iris AM Huijben, Taco Cohen
Overparameterisation and worst-case generalisation: friend or foe?
Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
PAC Confidence Predictions for Deep Neural Network Classifiers
Sangdon Park, Shuo Li, Insup Lee et al.