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Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge
Matt Gardner and Jayant KrishnamurthyAAAI • 2017 Traditional semantic parsers map language onto compositional, executable queries in a fixed schema. This map- ping allows them to effectively leverage the information con- tained in large, formal knowledge bases (KBs, e.g., Freebase) to answer questions, but…Probabilistic Neural Programs
Kenton W. Murray and Jayant KrishnamurthyNIPS • NAMPI Workshop • 2016 We present probabilistic neural programs, a framework for program induction that permits flexible specification of both a computational model and inference algorithm while simultaneously enabling the use of deep neural networks. Probabilistic neural programs…Designing AI Systems that Obey Our Laws and Values
Amitai Etzioni and Oren EtzioniCACM • 2016 Operational AI systems (for example, self-driving cars) need to obey both the law of the land and our values. We propose AI oversight systems ("AI Guardians") as an approach to addressing this challenge, and to respond to the potential risks associated with…Tables as Semi-structured Knowledge for Question Answering
Sujay Kumar Jauhar, Peter D. Turney, Eduard HovyACL • 2016 Question answering requires access to a knowledge base to check facts and reason about information. Knowledge in the form of natural language text is easy to acquire, but difficult for automated reasoning. Highly-structured knowledge bases can facilitate…Actions ~ Transformations
Xiaolong Wang, Ali Farhadi, and Abhinav GuptaCVPR • 2016 What defines an action like “kicking ball”? We argue that the true meaning of an action lies in the change or transformation an action brings to the environment. In this paper, we propose a novel representation for actions by modeling an action as a…Adaptive Concentration Inequalities for Sequential Decision Problems
Shengjia Zhao, Enze Zhou, Ashish Sabharwal, and Stefano ErmonNIPS • 2016 A key challenge in sequential decision problems is to determine how many samples are needed for an agent to make reliable decisions with good probabilistic guarantees. We introduce Hoeffding-like concentration inequalities that hold for a random, adaptively…A Diagram Is Worth A Dozen Images
Aniruddha Kembhavi, Mike Salvato, Eric Kolve, Minjoon Seo, Hannaneh Hajishirzi, and Ali FarhadiECCV • 2016 Diagrams are common tools for representing complex concepts, relationships and events, often when it would be difficult to portray the same information with natural images. Understanding natural images has been extensively studied in computer vision, while…Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects
Hessam Bagherinezhad, Hannaneh Hajishirzi, Yejin Choi, and Ali FarhadiAAAI • 2016 Human vision greatly benefits from the information about sizes of objects. The role of size in several visual reasoning tasks has been thoroughly explored in human perception and cognition. However, the impact of the information about sizes of objects is yet…A Task-Oriented Approach for Cost-sensitive Recognition
Roozbeh Mottaghi, Hannaneh Hajishirzi, and Ali FahradiCVPR • 2016 With the recent progress in visual recognition, we have already started to see a surge of vision related real-world applications. These applications, unlike general scene understanding, are task oriented and require specific information from visual data…Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference
Tudor Achim, Ashish Sabharwal, and Stefano ErmonICML • 2016 Random projections have played an important role in scaling up machine learning and data mining algorithms. Recently they have also been applied to probabilistic inference to estimate properties of high-dimensional distributions; however , they all rely on…