Modeling Ecosystems from Genome to Society – A symposium presenting how an international consortium that is working to build the first full-scale simulation of a complex social-ecological system. The Island Digital Ecosystem Avatar (IDEA) is an open science initiative to build use-oriented simulations (avatars) of entire systems starting with the islands of Tetiaroa and Moorea, […]
Today, one can Lyft a ride and AirBnb home away from home all in minutes. However, when comes to planning for our children’s enrichment activities, it takes us poor parents hours and days. Now 6crickets.com is going to change all that. 6crickets offers one easy stop for parents to discover, schedule, book and share children’s […]
Unlike traditional machine learning methods, humans often learn from natural language instruction. As users become increasingly accustomed to interacting with computer devices using speech, their interest in instructing these devices in natural language is likely to grow. We present our Learning by Instruction Agent (LIA), an intelligent personal agent that users can teach to perform […]
The design of fast, scalable, and correct concurrent systems remains a notoriously difficult task. Particularly problematic is the design of fast and scalable concurrent search data structures, which lie at the core of many modern systems. In this talk, I will present generic solutions to address this problem. I will first present a set of […]
Social multimedia refers to the multimedia content generated by social network users for social interactions. The increasing popularity of online social networks accumulates large amount of social network activity records, which makes the analysis of online social activities possible. The large-scale data have attracted people from both industrial and academic to mine interesting patterns from […]
Social multimedia refers to the multimedia content generated by social network users for social interactions. The increasing popularity of online social networks accumulates large amount of social network activity records, which makes the analysis of online social activities possible. The large-scale data have attracted people from both industrial and academic to mine interesting patterns from […]
The DISCO Nets is a new type of probabilistic model for estimating the conditional distribution over a complex structured output given an input. DISCO Nets allows efficient sampling from a posterior distribution parametrised by a neural network. During training, DISCO Nets are learned by minimising the dissimilarity coefficient between the true distribution and the estimated […]
Deep generative models have been wildly successful at learning coherent latent representations for continuous data such as video and audio. However, generative modeling of discrete data such as arithmetic expressions and molecular structures still poses significant challenges. Crucially, state-of-the-art methods often produce outputs that are not valid. We make the key observation that frequently, discrete […]
Bayesian optimisation (BO) is an optimisation method which incrementally builds a statistical model of the objective function to refine its search. Unfortunately, due to the curse of dimensionality, BO can fail to converge in problems with many dimensions. In this talk, I will show how better priors for BO can result in orders of magnitude […]
We present an algorithm for policy search in stochastic dynamical systems using model-based reinforcement learning. The system dynamics are described with Bayesian neural networks (BNNs) that include stochastic input variables. These input variables allow us to capture complex statistical patterns in the transition dynamics (e.g. multi-modality and heteroskedasticity), which are usually missed by alternative modeling […]
Recently, a new document metric called the word mover’s distance (WMD) has been proposed with unprecedented results on kNN-based document classification. The WMD elevates high-quality word embeddings to a document metric by formulating the distance between two documents as an optimal transport problem between the embedded words. However, the document distances are entirely unsupervised and […]
Three years ago, James Lloyd and I presented the Automatic Statistician at the joint MSR Cambridge machine learning meeting. The aim of this project is to automate the exploratory analysis and interpretation of data. Although progress has been slow, the project has not been dormant. We have completely refactored the code and extended the scope […]
