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(opens in new tab)Researchers have for years sought to understand the way opinions are formed and disseminated throughout social settings. Is there such a thing as the wisdom of the crowd?
New research presented at this year’s International Joint Conference on Artificial Intelligence (opens in new tab) examines crowd wisdom in the context of social networks — specifically the ever-important restaurant critiques.
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From studying how to identify gender bias in Hindi to uncovering AI-related risks for workers, Microsoft is making key contributions towards advancing the state of the art in responsible AI research. Check out their work at ACM FAccT 2024.
How Robust is the Wisdom of the Crowds? (opens in new tab) is just one of the 20 papers Microsoft researchers and their artificial intelligence collaborators from around the world will present at the biannual conference, which begins Saturday in Buenos Aires. As the main international gathering of AI researchers, its proceedings span multiple disciplines, including machine learning (opens in new tab), computational sustainability and even the arts.
Eric Horvitz (opens in new tab), renowned for his work in artificial intelligence and a distinguished scientist and managing director of the Redmond research lab (opens in new tab), contributed to two research papers being presented at IJCAI:
- Metareasoning for Planning Under Uncertainty (opens in new tab) describes the latest advance in a long tradition of research by Horvitz on giving computing systems the ability to do self-reflection or “metareasoning,” methods that can give computers the ability to observe and guide their own problem solving. The new work shows how metareasoning can guide the planning of long sequences of actions in challenging, time-critical environments.
- Information Gathering in Networks via Active Exploration (opens in new tab) presents a new algorithm, NETEXP, that could vastly improve search results on large networks such as the Internet.
Above: Eric Horvitz discusses the future of artificial intelligence at the 2015 Faculty Summit (opens in new tab).
Watch his full AI discussion with MIT’s Josh Tenebaum (opens in new tab).
Microsoft contributions to research presented at IJCAI-15
Offline Sketch Parsing via Shapeness (opens in new tab) Estimation (opens in new tab) (1.7 MB .pdf)
Microsoft contributors: Changhu Wang, Yong Rui
Cross-Domain Collaborative Filtering with Review Text (opens in new tab) (2.0 MB .pdf)
Microsoft contributor: Chin-Yew Lin
A Hybrid Neural Model for Type Classification of Entity Mentions (opens in new tab) (443 KB .pdf)
Microsoft contributors: Furu Wei; Hong Sun, Ming Zhou
Non-Myopic Negotiators See What’s Best (opens in new tab) (466 KB .pdf)
Microsoft contributors: Yoram Bachrach, Ian Kash, Peter Key
Maximum Satisfiability using Cores and Correction (opens in new tab) Sets (opens in new tab) (519 KB .pdf)
Microsoft contributor: Nikolaj Bjorner
Efficient Algorithms with Performance Guarantees for the Stochastic Multiple-Choice Knapsack Problem (opens in new tab) (abstract and download link)
Microsoft contributors: Yingce Xia, Tao Qin
Compositional Program Synthesis from Natural Language and Examples (opens in new tab) (138 KB .pdf)
Microsoft contributors: Mohammad Raza, Sumit Gulwani, Natasa Milic-Frayling
Selling Reserved Instances in Cloud Computing (opens in new tab) (451 KB .pdf)
Microsoft contributors: Weidong Ma, Tao Qin, Tieyan Liu
Personalized Mathematical Word Problem Generation (opens in new tab) (590 KB .pdf)
Microsoft contributor: Sumit Gulwani
The Right to Obscure: a Mechanism and Initial Evaluation (opens in new tab) (519 KB .pdf)
Microsoft contributor: Jaron Lanier
FlashNormalize: Programming by Examples for Text Normalization (opens in new tab) (329 KB .pdf)
Microsoft contributor: Sumit Gulwani
Quantized Correlation Hashing for Fast Cross-modal Search (opens in new tab) (523 KB .pdf)
Microsoft contributor: Jingdong Wang
Mobile Query Recommendation via Tensor Function Learning (opens in new tab) (1.2 MB .pdf)
Microsoft contributor: Xing Xie
Thompson Sampling for Budgeted Multi-armed Bandit (opens in new tab) (abstract and download link)
Microsoft contributors: Tao Qin, Tie-Yan Liu
Did you know?: Mining Interesting Trivia for Entities from Wikipedia (opens in new tab) (340 KB .pdf)
Microsoft contributors: Manoj Kumar Chinnakotla, Puneet Garg
Artificial intelligence