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2010 – 2019
- 2019
[c10]Daniel McNamara, Cheng Soon Ong, Robert C. Williamson:
Costs and Benefits of Fair Representation Learning. AIES 2019: 263-270- [c9]Daniel McNamara:
Equalized Odds Implies Partially Equalized Outcomes Under Realistic Assumptions. AIES 2019: 313-320 - [c8]Daniel McNamara:
Algorithmic Stereotypes: Implications for Fairness of Generalizing from Past Data. AIES 2019: 535-536 - 2018
- [c7]Ali Momeni, Daniel McNamara, Jesse Stiles:
MOM: an Extensible Platform for Rapid Prototyping and Design of Electroacoustic Instruments. NIME 2018: 65-71 - [c6]Ali Momeni, Daniel McNamara:
MOD: A Portable Instrument for Mixing Analog and Digital Drawing for Live Cinema. TEI 2018: 460-469 - 2017
- [c5]Daniel McNamara, Maria-Florina Balcan:
Performance guarantees for transferring representations. ICLR (Workshop) 2017 - [c4]Daniel McNamara, Maria-Florina Balcan:
Risk Bounds for Transferring Representations With and Without Fine-Tuning. ICML 2017: 2373-2381 - [c3]Spencer Salazar, Sarah Reid, Daniel McNamara:
The fragment string. NIME 2017: 381-386 - [i2]Daniel McNamara, Cheng Soon Ong, Robert C. Williamson:
Provably Fair Representations. CoRR abs/1710.04394 (2017) - 2016
- [c2]Daniel McNamara, Ajay Kapur:
Roulette: A Customized Circular Sequencer for Generative Music. ICMC 2016 - [i1]Daniel McNamara, Cheng Soon Ong, Robert C. Williamson:
A Modular Theory of Feature Learning. CoRR abs/1611.03125 (2016) - 2014
- [j1]Carolyn Strange, Daniel McNamara, Josh Wodak, Ian Wood:
Mining for the Meanings of a Murder: The Impact of OCR Quality on the Use of Digitized Historical Newspapers. Digit. Humanit. Q. 8(1) (2014) - 2013
- [c1]Daniel McNamara, Paul Wong
, Peter Christen, Kee Siong Ng:
Predicting High Impact Academic Papers Using Citation Network Features. PAKDD Workshops 2013: 14-25
Coauthor Index
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