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05-08
Bridging the gap between cloud infrastructure and Production Data Science
Over the last decade, data scientists have mastered the process of building machine learning models. The next frontier is putting these models into production: using them to consistently generate high...
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05-08
Reducing the Ever-growing Cost of Large-Scale Machine Learning Services
The recent success of machine learning (ML) has dramatically benefited from the exponential growth of ML model capacity. However, the enormous capacity of ML models also leads to a significantly highe...
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05-08
Query Complexity of Least Absolute Deviation Regression via Robust Uniform Convergence
Consider a regression problem where the learner is given a large collection of d-dimensional data points but can only query a small subset of the real-valued labels. How many queries are needed to obt...
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05-08
From the breakdown of topological quantum memory to mixed-state topological order
Topological quantum memory can protect information against local errors up to finite error thresholds. Such thresholds are usually determined via the decoding algorithms rather than the intrinsic prop...
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05-08
Algorithms for simulating thermal quantum many-body systems: quantum computation, tensor networks and neural networks
Simulation of quantum many-body systems is extremely challenging, as computational resources (time, memory) grow exponentially with system size. In this talk, I will introduce one classical and one qu...
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05-08
QoS-Aware Resource Management in the Cloud: From Academia to Industry
Most cloud facilities operate at very low utilization. Naive colocation of more workloads on the same server node leads to severe quality-of-service (QoS) degradation of cloud services. It is challeng...