Asia
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates
Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
Neural Information Processing Systems http://nips.cc/
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding
People are relying on AI agents to assist them with various tasks.
Learning to Scaffold: Optimizing Model Explanations for Teaching
Patrick Fernandes, Marcos Treviso, Danish Pruthi, Andrรฉ F. T. Martins, Graham Neubig
First, a student model is trained to recover the classifier'spredictions andtomatch theexplanations givenbytheexplainer.
Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity Attacks
Lixin Fan, Kam Woh Ng, Chee Seng Chan
Extensiveexperimental results justify the effectiveness oftheproposed passport-based DNNownership verification schemes.
Multi-Layered Gradient Boosting Decision Trees
Ji Feng, Yang Yu, Zhi-Hua Zhou
Multi-layered distributed representation is believed to be the key ingredient of deep neural networks especially in cognitive tasks like computer vision.
RethinkingAlignmentinVideoSuper-Resolution Transformers
Nevertheless, such designs will dramatically increase the computational burden, and cannot deal with large motions. Therefore, we propose a new and efficient alignment method called patch alignment, which aligns image patches instead ofpixels.
DropMax: Adaptive Variational Softmax
Hae Beom Lee, Juho Lee, Saehoon Kim, Eunho Yang, Sung Ju Hwang
Neural Information Processing Systems http://nips.cc/
Adversarial training for free!
Ali Shafahi, Mahyar Najibi, Mohammad Amin Ghiasi, Zheng Xu, John Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein
Neural Information Processing Systems http://nips.cc/