Events

ARISE Program – Validate

Progressively applying Gaussian noise transforms complex data distributions to approximately Gaussian. Reversing this dynamic defines a generative model. When the forward noising process is given by a Stochastic Differential Equation (SDE), Song et al. (2021) demonstrate how the time inhomogeneous drift of the associated reverse-time SDE may be estimated using score-matching. A limitation of this approach is that the forward-time SDE must be run for a sufficiently long time for the final distribution to be approximately Gaussian. In contrast, solving the Schrödinger Bridge problem (SB), i.e. an entropy-regularized optimal transport problem on path spaces, yields diffusions which generate samples from the data distribution in finite time. We present Diffusion SB (DSB), an original approximation of the Iterative Proportional Fitting (IPF) procedure to solve the SB problem, and provide theoretical analysis along with generative modeling experiments. The first DSB iteration recovers the methodology proposed by Song et al. (2021), with the flexibility of using shorter time intervals, as subsequent DSB iterations reduce the discrepancy between the final-time marginal of the forward (resp. backward) SDE with respect to the prior (resp. data) distribution. Beyond generative modeling, DSB offers a widely applicable computational optimal transport tool as the continuous state-space analogue of the popular Sinkhorn algorithm (Cuturi, 2013).

HASS Colloquium Series: Achieving the digital equity for students with special educational needs by Dr. Sin Kuen Fung Kenneth

James Chong (The Tesseract, NCS Group) – “How to Sell a Better Mousetrap” – How Advanced Analytics and Generative AI is changing the world and how to convince people to use it

According to a UN report from 2022, time is running out to limit temperature rises to 1.5C by 2050. Around $3.5 trillion climate investment per year is needed to build the net zero economy by 2050. This investment is possible only with significant contribution from the private financial sector. This is specifically the case in emerging markets, where public investments aren’t growing as quickly as needed to meet climate targets. There are a quite a few issues related to data disclosures, transparency and complexities, which needs to be tackled in order to efficiently manage the private sustainable investment need. Data Science and Innovation can help tackle these issues and assist the community is making quick and accurate investment decisions.

ARISE Program – Validate

Pye Sone Kyaw (Government Technology Agency) – Leveraging AI/ML for Transformative Solutions in Diverse Industries

Data is now unanimously considered a key firm asset for enabling better operational decisions. However, data-driven decisions can inadvertently expose private data, leaving firms vulnerable to unforeseen danger. How to manage data security risks by protecting data from being inferred from observable decisions thus becomes an important question. In this paper, we focus on data security in supply chains due to their data-intensive nature. Specifically, we examine a data-driven contextual newsvendor problem. To quantify and ensure data security, we adopt the notion of differential privacy, a mathematically rigorous measure of data security that limits an attacker’s inference accuracy. Employing convolution smoothing and noise injection, we propose several differentially private algorithms that provably guarantee both data security and asymptotic optimality with (near) optimal rates. In the non-asymptotic regime, we further identify three drivers of the cost of data security; namely, dataset size, context, and number of products. This finding suggests that gathering more data, collecting detailed context, and pooling data from multiple products can lower data security cost. Lastly, we examine the impact of a newsvendor’s private algorithms on supply chain partners. We discover additional distortion to the demand signaling process and lower profit share for an upstream supplier.

ARISE Program – Validate

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