Deep Learning
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru
Neural Information Processing Systems http://nips.cc/
Learning from Label Proportions with Generative Adversarial Networks
Jiabin Liu, Bo Wang, Zhiquan Qi, YingJie Tian, Yong Shi
Neural Information Processing Systems http://nips.cc/
Learning sparse neural networks via sensitivity-driven regularization
Enzo Tartaglione, Skjalg Lepsøy, Attilio Fiandrotti, Gianluca Francini
Neural Information Processing Systems http://nips.cc/
Critical initialisation for deep signal propagation in noisy rectifier neural networks
Arnu Pretorius, Elan van Biljon, Steve Kroon, Herman Kamper
Neural Information Processing Systems http://nips.cc/
L VM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching Duy M. H. Nguyen
Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data.
How Many Samples are Needed to Estimate a Convolutional Neural Network?
Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Russ R. Salakhutdinov, Aarti Singh
Neural Information Processing Systems http://nips.cc/