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IBM Journal of Research and Development, Volume 63
Volume 63, Number 1, January - February 2019
- Bryan Wiltgen
, Ashok K. Goel:
A computational theory of evaluation in creative design. 1:1-1:11 - Lav R. Varshney
Mathematical limit theorems for computational creativity. 2:1-2:12 - S. Agrawal, Anush Sankaran
What is deemed computationally creative? 3:1-3:12 - Elham Khabiri
Cognitive color palette creation using client message and color psychology. 4:1-4:10 - Pegah Karimi
A computational model for visual conceptual blends. 5:1-5:10 - Anupama Ray
Creative tagline generation framework for product advertisement. 6:1-6:10 - Lav R. Varshney
A big data approach to computational creativity: The curious case of Chef Watson. 7:1-7:18 - Pablo Gervás, Eugenio Concepción, Carlos León
The long path to narrative generation. 8:1-8:10 - Pedro Martins
Computational creativity infrastructure for online software composition: A conceptual blending use case. 9:1-9:17
Volume 63, Numbers 2/3, March - May 2019
- R. Viswanathan
Blockchain Solution Reference Architecture (BSRA). 1:1-1:12 - Yacov Manevich, Artem Barger, Yoav Tock:
Endorsement in Hyperledger Fabric via service discovery. 2:1-2:9 - Fabrice Benhamouda, Shai Halevi
Supporting private data on Hyperledger Fabric with secure multiparty computation. 3:1-3:8 - Venkat S. K. Balagurusamy, Cyril Cabral, Srikumar Coomaraswamy, Emmanuel Delamarche, Donna N. Dillenberger
Crypto anchors. 4:1-4:12 - Donna Dillenberger
Blockchain analytics and artificial intelligence. 5:1-5:14 - Takaaki Tateishi, Sachiko Yoshihama, Naoto Sato, Shin Saito:
Automatic smart contract generation using controlled natural language and template. 6:1-6:12 - Chandra Narayanaswami, Raj Nooyi, Srinivasa Raghavan Govindaswamy, R. Viswanathan:
Blockchain anchored supply chain automation. 7:1-7:11 - Francisco Curbera, Daniel M. Dias, Vahan Simonyan Simonyan, Woong A. Yoon, Alex Casella:
Blockchain: An enabler for healthcare and life sciences transformation. 8:1-8:9
Volume 63, Numbers 4/5, July - September 2019
- Avinash Balakrishnan, Djallel Bouneffouf, Nicholas Mattei
Using multi-armed bandits to learn ethical priorities for online AI systems. 1:1-1:13 - Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei
Teaching AI agents ethical values using reinforcement learning and policy orchestration. 2:1-2:9 - Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney:
Fairness GAN: Generating datasets with fairness properties using a generative adversarial network. 3:1-3:9 - Rachel K. E. Bellamy
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. 4:1-4:15 - Biplav Srivastava, Francesca Rossi:
Rating AI systems for bias to promote trustable applications. 5:1-5:9 - Matthew Arnold, Rachel K. E. Bellamy, Michael Hind, Stephanie Houde, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, Karthikeyan Natesan Ramamurthy, Alexandra Olteanu, David Piorkowski
FactSheets: Increasing trust in AI services through supplier's declarations of conformity. 6:1-6:13 - Daphne L. Coates, Andrew Martin:
An instrument to evaluate the maturity of bias governance capability in artificial intelligence projects. 7:1-7:15 - Maria Y. Rodriguez
Bridging the gap: Social work insights for ethical algorithmic decision-making in human services. 8:1-8:8 - Katharina Simbeck
HR analytics and ethics. 9:1-9:12
Volume 63, Number 6, November - December 2019
- Minsik Cho, Ulrich Finkler, Mauricio J. Serrano, David S. Kung, Hillery C. Hunter:
BlueConnect: Decomposing all-reduce for deep learning on heterogeneous network hierarchy. 1:1-1:11 - David E. Womble, Mallikarjun Shankar
Early experiences on Summit: Data analytics and AI applications. 2:1-2:9 - Saugata Ghose
Processing-in-memory: A workload-driven perspective. 3:1-3:19 - Saibal Mukhopadhyay, Yun Long, Burhan Ahmad Mudassar, C. S. Nair, Bartlet H. DeProspo, Hakki Mert Torun, M. Kathaperumal, V. Smet, Duckhwan Kim, Sudhakar Yalamanchili, Madhavan Swaminathan:
Heterogeneous integration for artificial intelligence: Challenges and opportunities. 4:1 - Subramanian S. Iyer, SivaChandra Jangam
Silicon interconnect fabric: A versatile heterogeneous integration platform for AI systems. 5:1-5:16 - Alon Amid
Co-design of deep neural nets and neural net accelerators for embedded vision applications. 6:1-6:14 - Evangelos Eleftheriou, Manuel Le Gallo, S. R. Nandakumar, Christophe Piveteau
Deep learning acceleration based on in-memory computing. 7:1-7:16 - Hung-Yang Chang, Pritish Narayanan
AI hardware acceleration with analog memory: Microarchitectures for low energy at high speed. 8:1-8:14 - Elliot J. Fuller, Yiyang Li, Christopher H. Bennett, Scott T. Keene
Redox transistors for neuromorphic computing. 9:1-9:9 - Shubham Jain, Aayush Ankit, Indranil Chakraborty, Tayfun Gokmen, Malte J. Rasch, Wilfried Haensch, Kaushik Roy, Anand Raghunathan
Neural network accelerator design with resistive crossbars: Opportunities and challenges. 10:1-10:13
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