Country
Sample-efficient Bayesian Optimisation Using Known Invariances Theodore Brown
Bayesian optimisation (BO) is a powerful framework for global optimisation of costly functions, using predictions from Gaussian process models (GPs).
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition
However, it is important to consider users' privacy in the dataset, since results from data
Ease-of-Teaching and Language Structure from Emergent Communication
Some leveloflanguage structure (e.g., compositionality) has been found in the learned communication protocols.
Reward learning from human preferences and demonstrations in Atari
Borja Ibarz, Jan Leike, Tobias Pohlen, Geoffrey Irving, Shane Legg, Dario Amodei
Neural Information Processing Systems http://nips.cc/
5598cf1b2905a26ddb863e6705588327-Paper-Conference.pdf
Video understanding relies on accurate action detection for temporal analysis.
Geometry-Aware Recurrent Neural Networks for Active Visual Recognition
Ricson Cheng, Ziyan Wang, Katerina Fragkiadaki
Cross-object occlusions remain an important source of failures for current state-of-the-art object detectors [29],which, despite their formidable performance increase inrecent years, still carrythe biases and idiosyncrasies of the data they were trained on [16]: static images from Imagenet and COCOdatasets.
Deep imitation learning for molecular inverse problems
Neural Information Processing Systems http://nips.cc/
