James Y Zou

22 papers · 2013–2023 · 1 conference · across top CS/AI conferences

Achievements

+14 more ↓

🏃 Academic Marathon (10) 🐝 Cross-Pollinator (13) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌈 Renaissance Researcher (10)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (4) 🏠 Conference Loyalist (22) 📛 The Namer 🏆 Keyword Champion 🌱 Topic Pioneer 👥 Mega-Team (47) 📈 Trend Setter ⚡ Prolific Year (7) 🗃️ Keyword Collector (112) ❓ The Questioner 🔥 Unstoppable (8) 💎 Century Club (22)

Conferences

NIPS (22)

Top co-authors

Lingjiao Chen (4) Yongchan Kwon (3) Linjun Zhang (3) Matei Zaharia (3) Amirata Ghorbani (3) Chelsea Finn (2) Evan Sabri Eyuboglu (2) Kailas Vodrahalli (2) Mert Yuksekgonul (2) Serena Yeung (2)

Research topics

Applications (1)

Keywords

contrastive learning (3) representation learning (3) model calibration (2) shapley value (2) feature importance (2) concept-based explanation (2) multi-armed bandit (2) confidence calibration (2) model interpretation (2) neural network (2) data quality (2) feature attribution (2) k-means clustering (1) sentiment analysis (1) game theory (1) domain adaptation (1) offline reinforcement learning (1) transfer learning (1) topic modeling (1) benchmark suite (1)

Papers

DataPerf: Benchmarks for Data-Centric AI Development NIPS 2023 Beyond Confidence: Reliable Models Should Also Consider Atypicality NIPS 2023 TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter NIPS 2023 Factorized Contrastive Learning: Going Beyond Multi-view Redundancy NIPS 2023 OpenDataVal: a Unified Benchmark for Data Valuation NIPS 2023 Uncalibrated Models Can Improve Human-AI Collaboration NIPS 2022 C-Mixup: Improving Generalization in Regression NIPS 2022 Estimating and Explaining Model Performance When Both Covariates and Labels Shift NIPS 2022 Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning NIPS 2022 SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained debugging and analysis NIPS 2022 HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions NIPS 2022 WeightedSHAP: analyzing and improving Shapley based feature attributions NIPS 2022 Adversarial Training Helps Transfer Learning via Better Representations NIPS 2021 Neuron Shapley: Discovering the Responsible Neurons NIPS 2020 FrugalML: How to use ML Prediction APIs more accurately and cheaply NIPS 2020 MOPO: Model-based Offline Policy Optimization NIPS 2020 Making AI Forget You: Data Deletion in Machine Learning NIPS 2019 Towards Automatic Concept-based Explanations NIPS 2019 Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders NIPS 2018 NeuralFDR: Learning Discovery Thresholds from Hypothesis Features NIPS 2017 Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings NIPS 2016 Contrastive Learning Using Spectral Methods NIPS 2013