Videos

Sentiment and Emotion Analysis for Social Multimedia: Methodologies and Applications

8 hours 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

3 days 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

3 days 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

3 days 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

3 days 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

5 days 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

7 days 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

7 days 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 […]

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

1 week 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 […]

Microsoft Security Risk Detection Helps Digital Transaction Management company DocuSign

1 week ago
Taking paper-driven processes online isn’t easy – but keeping it secure is a whole other matter. To help, global eSignature and Digital Transaction Management (DTM) leader DocuSign recently used Microsoft Security Risk Detection to provide additional assurance, ensuring its code is always ready to match today’s security threats. See more on this video at www.microsoft.com/en-us/research/video/microsoft-security-risk-detection-helps-digital-transaction-management-company-docusign/

Microsoft Security Risk Detection Helps Digital Transaction Management company DocuSign

1 week ago
Taking paper-driven processes online isn’t easy – but keeping it secure is a whole other matter. To help, global eSignature and Digital Transaction Management (DTM) leader DocuSign recently used Microsoft Security Risk Detection to provide additional assurance, ensuring its code is always ready to match today’s security threats.

Automating and Testing Program Transformations using Program Synthesis

1 week ago
Automatic program transformation tools can be valuable for programmers to help them with refactoring tasks, and for Computer Science students in the form of tutoring systems that suggest repairs to programming assignments. However, manually implementing and testing catalogs of transformations is complex and time-consuming. In this talk, I will present two program synthesis-based techniques for […]