Technical Reports by Author
Theses by Author
ML Theses (with Joint Degrees)

2020 Series

CMU-ML-20-100
Probabilistic Single Cell Lineage Tracing
Chieh Lin, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-101
Reconstructing and Mining Signals: Algorithms and Applications
Hyun Ah Song, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-102
Provable, structured, and efficient methods for robustness of deep networks to adversarial examples
Eric Wong, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-103
Learning Collections of Functions
Emmanouil Antonios Platanios, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-104
Towards Efficient Automated Machine Learning
Liam Li, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-105
Structured Sparse Regression Methods for Learning from High-Dimensional Genomic Data
Micol Marchetti-Bowick, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-106
Data Decomposition for Constrained Visual Learning
Calvin Murdock, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-107
Towards Data-Efficient Machine Learning
Qizhe Xie, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-108
Learning and Decision Making from Diverse Forms of Information
Yichong Xu, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-109
Machine Learning and Multiagent Preferences
Ritesh Noothigattu, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-110
Learning DAGs with Continuous Optimization
Xun Zheng, Ph.D. Thesis
Abstract, .pdf

CMU-ML-20-111
Towards a Unified Framework for Learning and Reasoning
Han Zhao, Ph.D. Thesis
Abstract, .pdf

Return to: SCS Technical Report Collection