FEDERATED LEARNING WITH ONLY POSITIVE LABELS
|
2021 |
Yu, Felix X. |
LEARNING THE VALUATIONS OF A K-DEMAND AGENT
|
2021 |
Zhang, Hanrui |
A TREE-STRUCTURED DECODER FOR IMAGE-TO-MARKUP GENERATION
|
2021 |
Zhang, Jianshu |
RANDOM HYPERVOLUME SCALARIZATIONS FOR PROVABLE MULTI-OBJECTIVE BLACK BOX OPTIMIZATION
|
2021 |
Golovin, D. |
PRIVATELY LEARNING MARKOV RANDOM FIELDS
|
2021 |
Zhang, Huanyu |
LEARNING STRUCTURED LATENT FACTORS FROM DEPENDENT DATA:A GENERATIVE MODEL FRAMEWORK FROM INFORMATION-THEORETIC PERSPECTIVE
|
2021 |
Zhang, Ruixiang |
ATTACKS WHICH DO NOT KILL TRAINING MAKE ADVERSARIAL LEARNING STRONGER
|
2021 |
Zhang, Jingfeng |
LEARNING WITH FEATURE AND DISTRIBUTION EVOLVABLE STREAMS
|
2021 |
Zhang, Zhen-Yu |
VARIANCE REDUCTION IN STOCHASTIC PARTICLE-OPTIMIZATION SAMPLING
|
2021 |
Zhang, Jianyi |
SMALLER, MORE ACCURATE REGRESSION FORESTS USING TREE ALTERNATING OPTIMIZATION
|
2021 |
Zharmagambetov, Arman |
SHARP COMPOSITION BOUNDS FOR GAUSSIAN DIFFERENTIAL PRIVACY VIA EDGEWORTH EXPANSION
|
2021 |
Zheng, Qinging |
ERROR-BOUNDED CORRECTION OF NOISY LABELS
|
2021 |
Zheng, Songzhu |
WHAT CAN LEARNED INTRINSIC REWARDS CAPTURE?
|
2021 |
Zheng, Zeyu |
DIVIDE, CONQUER, AND COMBINE: A NEW INFERENCE STRATEGY FOR PROBABILISTIC PROGRAMS WITH STOCHASTIC SUPPORT
|
2021 |
Zhou, Yuan |
GO WIDE, THEN NARROW: EFFICIENT TRAINING OF DEEP THIN NETWORKS
|
2021 |
Zhou, Denny |
HYBRID STOCHASTIC-DETERMINISTIC MINIBATCH PROXIMAL GRADIENT: LESS-THAN-SINGLE- PASS OPTIMIZATION WITH NEARLY OPTIMAL GENERALIZATION
|
2021 |
Zhou, Pan |
ADAPTIVE CHECKPOINT ADJOINT METHOD FOR GRADIENT ESTIMATION IN NEURAL ODE
|
2021 |
Zhuang, Juntang |
TRANSFORMER HAWKES PROCESS
|
2021 |
Zao, Li. S. |
INFLUENZA FORECASTING FRAMEWORK BASED ON GAUSSIAN PROCESSES
|
2021 |
Zimmer, C. |
A GENERAL RECURRENT STATE SPACE FRAMEWORK FOR MODELING NEURAL DYNAMICS DURING DECISION-MAKING
|
2021 |
Zoltowski, David M. |