19 citations · 24 across the 4 of their papers we have counts for
5 papers
Analogy Mining for Specific Design Needs
Karni Gilon, Felicia Y Ng, Joel Chan +3
Finding analogical inspirations in distant domains is a powerful way of solving problems. However, as the number of inspirations that could be matched and the dimensions on which t…
Ballpark Crowdsourcing: The Wisdom of Rough Group Comparisons
Tom Hope, Dafna Shahaf
Crowdsourcing has become a popular method for collecting labeled training data. However, in many practical scenarios traditional labeling can be difficult for crowdworkers (for exa…
A Machine Learning Approach to Routing
Asaf Valadarsky, Michael Schapira, Dafna Shahaf +1
Can ideas and techniques from machine learning be leveraged to automatically generate "good" routing configurations? We investigate the power of data-driven routing protocols. Our…
Accelerating Innovation Through Analogy Mining
Tom Hope, Joel Chan, Aniket Kittur +1
The availability of large idea repositories (e.g., the U.S. patent database) could significantly accelerate innovation and discovery by providing people with inspiration from solut…
Ballpark Learning: Estimating Labels from Rough Group Comparisons
Tom Hope, Dafna Shahaf
We are interested in estimating individual labels given only coarse, aggregated signal over the data points. In our setting, we receive sets ("bags") of unlabeled instances with co…