Idea Date Science – Session 1

3 days ago
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, […]

Artificial Intelligence to Ease Parents’ Pain in Summer Camp Planning

4 days ago
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 is going to change all that. 6crickets offers one easy stop for parents to discover, schedule, book and share children’s […]

Machine Learning from Verbal Instruction

5 days ago
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 […]

Universally Scalable Concurrent Search Data Structures

5 days ago
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 […]

Sentiment and Emotion Analysis for Social Multimedia: Methodologies and Applications

5 days ago
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 […]

DISCO Nets: DIssimilarity COefficient Networks

1 week ago
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 […]

Grammar Variational Autoencoder

1 week ago
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 in many dimensions with bespoke models

1 week ago
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 […]

Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks

1 week ago
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 […]

Accountable Algorithms

1 week ago
Important decisions about people are increasingly made by algorithms: Votes are counted; voter rolls are purged; financial aid decisions are made; taxpayers are chosen for audits; air travelers are selected for enhanced search; credit eligibility decisions are made. Citizens, and society as a whole, have an interest in making these processes more transparent. Yet the […]

Nonlinear ICA using temporal structure: a principled framework for unsupervised deep learning

2 weeks ago
Unsupervised learning, in particular learning general nonlinear representations, is one of the deepest problems in machine learning. Estimating latent quantities in a generative model provides a principled framework, and has been successfully used in the linear case, e.g. with independent component analysis (ICA) and sparse coding. However, extending ICA to the nonlinear case has proven […]

Predicting 3D Volume and Depth from a Single View

2 weeks ago
A single glimpse is hardly enough to triangulate the 3D shapes of a scene. However, training examples are readily available, so statistical models can be trained to map appearance to shape. The details matter, because 3D shapes have different representations and can have many degrees of freedom, and training data is rarely as clean as […]