training label
Multi-Resolution Weak Supervision for Sequential Data
Paroma Varma, Frederic Sala, Shiori Sagawa, Jason Fries, Daniel Fu, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, Christopher Ré
Neural Information Processing Systems http://nips.cc/
- North America > United States > Louisiana > Orleans Parish > New Orleans (0.04)
- North America > United States > Hawaii > Honolulu County > Honolulu (0.04)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- (4 more...)
Self-AdaptiveTraining: beyondEmpiricalRisk Minimization
This problem is important to robustly learning from data that are corrupted by,e.g., random noise and adversarial examples. The standard empirical risk minimization (ERM) for such data, however, may easily overfit noise and thus suffers from sub-optimal performance. In this paper, we observe that model predictions can substantially benefit the training process: self-adaptive training significantly mitigates the overfitting issue and improves generalization over ERM under both random and adversarial noise.
- North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
- Asia > Middle East > Jordan (0.04)
- North America > United States > Illinois > Champaign County > Urbana (0.04)
- Europe > Slovenia > Drava > Municipality of Benedikt > Benedikt (0.04)
Multi-Resolution Weak Supervision for Sequential Data
Paroma Varma, Frederic Sala, Shiori Sagawa, Jason Fries, Daniel Fu, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, Christopher Ré
Neural Information Processing Systems http://nips.cc/
- North America > United States > Louisiana > Orleans Parish > New Orleans (0.04)
- North America > United States > Hawaii > Honolulu County > Honolulu (0.04)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- (4 more...)
- Health & Medicine > Therapeutic Area (1.00)
- Government > Regional Government > North America Government > United States Government (1.00)
- Information Technology (0.93)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Natural Language (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
- Information Technology > Artificial Intelligence > Robots > Autonomous Vehicles (0.46)
Understanding Programmatic Weak Supervision via Source-aware Influence Function
These authors contributed equally to this work.
- North America > United States > Illinois > Champaign County > Urbana (0.04)
- Europe > Slovenia > Drava > Municipality of Benedikt > Benedikt (0.04)