Videos
See AI2's full collection of videos on our YouTube channel.Viewing 221-230 of 257 videos
Strategies and Principles for Distributed Machine Learning
February 16, 2016 | Eric XingThe rise of Big Data has led to new demands for Machine Learning (ML) systems to learn complex models with millions to billions of parameters that promise adequate capacity to digest massive datasets and offer powerful predictive analytics (such as high-dimensional latent features, intermediate representations…
Intelligible Machine Learning Models for HealthCare
February 9, 2016 | Rich CaruanaLocally normalized approaches for structured prediction, such as left-to-right parsing and sequence labeling, are attractive because of their simplicity, ease of training, and the flexibility in choosing features from observations. Combined with the power of neural networks, they have been widely adopted for NLP…
Probabilistic Models for Learning a Semantic Parser Lexicon
January 27, 2016 | Jayant KrishnamurthyLexicon learning is the first step of training a semantic parser for a new application domain, and the quality of the learned lexicon significantly affects both the accuracy and efficiency of the final semantic parser. Existing work on lexicon learning has focused on heuristic methods that lack convergence…
Machine Teaching
January 12, 2016 | Patrice SimardFor many ML problems, labeled data is readily available. The algorithm is the bottleneck. This is the ML researcher’s paradise! Problems that have fairly stable distributions and can accumulate large quantities of human labels over time have this property: Vision, Speech, Autonomous driving. Problems that have…
Adding Structure to Unstructured and Semi-structured Data
December 10, 2015 | Chandra BhagavatulaIn this talk, I will describe two systems designed to extract structured knowledge from unstructured and semi-structured data. First, I'll present an entity linking system for Web tables. Next, I'll talk about a key phrase extraction system that extracts a set of key concepts from a research article. Towards the…
Provable Guarantees for Non-convex and Convex Optimization in High Dimensions
November 3, 2015 | Hanie SedghiLearning with big data is akin to finding a needle in a haystack: useful information is hidden in high dimensional data. Optimization methods, both convex and nonconvex, require new thinking when dealing with high dimensional data, and I present two novel solutions.
Large Topic Models: Efficient Inference and Applications
September 14, 2015 | Doug DowneyIn this talk, I will introduce efficient methods for inferring large topic hierarchies. The approach is built upon the Sparse Backoff Tree (SBT), a new prior for latent topic distributions that organizes the latent topics as leaves in a tree. I will show how a document model based on SBTs can effectively infer…
Contextual LSTMs A step towards Hierarchial Language Modeling
September 10, 2015 | Shalini GhoshDocuments exhibit sequential structure at multiple levels of abstraction (e.g., sentences, paragraphs, sections). These abstractions constitute a natural hierarchy for representing the context in which to infer the meaning of words and larger fragments of text. In this talk, we present CLSTM (Contextual LSTM), an…
Unsupervised Alignment of Natural Language with Video
August 18, 2015 | Iftekhar NaimToday we encounter enormous amounts of video data, often accompanied with text descriptions (e.g., cooking videos and recipes, movies and shooting scripts). Extracting meaningful information from these multimodal sequences requires aligning the video frames with the corresponding text sentences. We address the…
Feature Generation from Knowledge Graphs
July 30, 2015 | Matt GardnerA lot of attention has recently been given to the creation of large knowledge bases that contain millions of facts about people, things, and places in the world. In this talk I present methods for using these knowledge bases to generate features for machine learning models. These methods view the knowledge base…