Education
Online Learning via the Differential Privacy Lens
Jacob D. Abernethy, Young Hun Jung, Chansoo Lee, Audra McMillan, Ambuj Tewari
Neural Information Processing Systems http://nips.cc/
Co-teaching: Robust training of deep neural networks with extremely noisy labels
Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, Masashi Sugiyama
Neural Information Processing Systems http://nips.cc/
Online Reciprocal Recommendation with Theoretical Performance Guarantees
Claudio Gentile, Nikos Parotsidis, Fabio Vitale
Neural Information Processing Systems http://nips.cc/
HIQL: Offline Goal-Conditioned RL with Latent States as Actions Seohong Park
We observe that part of this difficulty stems from the "signal-to-noise"
Efficient Online Portfolio with Logarithmic Regret
Haipeng Luo, Chen-Yu Wei, Kai Zheng
Neural Information Processing Systems http://nips.cc/
Adaptive Methods for Nonconvex Optimization
Manzil Zaheer, Sashank Reddi, Devendra Sachan, Satyen Kale, Sanjiv Kumar
The first prominent algorithms in this line of research isADAGRAD [7,22], which uses a per-dimension learning rate based on squared pastgradients.ADAGRADachievedsignificant performance gainsincomparison toSGDwhenthe gradientsaresparse.
Online Control with Adversarial Disturbance for Continuous-time Linear Systems
A major challenge in robotics is to deploy simulated controllers into real-world.
No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
Neural Information Processing Systems http://nips.cc/