Dan Ports (University of Washington)

Speaker:

Dan Ports

Today's most popular applications are deployed as massive-scale distributed systems in the datacenter. Keeping data consistent and available despite server failures and concurrent updates is a formidable challenge. Two well-known abstractions, strongly consistent replication and serializable transactions, can free developers from these challenges by transparently masking failures and treating complex updates as atomic units. Yet the conventional wisdom is that... Read More

[MLD Seminar] Jure Leskovec (Stanford University)

Speaker:

Jure Leskovec

Evaluating whether machines improve on human performance is one of the central questions of machine learning. However, there are many domains where the data is selectively labeled in the sense that the observed outcomes are themselves a consequence of the existing choices of the human decision-makers. For instance, in the context of judicial bail decisions, the outcome of whether a... Read More

[HCII Seminar] Michael Franklin (University of Chicago)

Speaker:

Mike Franklin

The “P“ in AMPLab stands for "People" and an important research thrust in the lab was on integrating human processing into analytics pipelines. Starting with the CrowdDB project on human-powered query answering and continuing into the more recent SampleClean and AMPCrowd/Clamshell projects, we have been investigating ways to maximize the benefit that can be obtained through involving people in data... Read More

[DB Seminar] Spring 2017: Alex Poms

Speaker:

Alex Poms

A growing number of visual computing applications depend on the analysis of large video collections. The challenge is that scaling applications to operate on these datasets requires highly efficient systems for pixel data access and parallel processing. Few programmers have the capability to operate efficiently at these scales, limiting the field's ability to explore new applications that analyze large video... Read More

[DB Seminar] Spring 2017: Xiangyao Yu

Speaker:

Xiangyao Yu

Strong consistency in parallel systems provides high programmability, but requires expensive coordination and scales poorly. This challenge exists in multiple layers of abstraction across the whole hardware and software stack. Examples include multicore processors, parallel transaction processing, and distributed systems. In this talk, I will introduce a simple primitive called logical leases to achieve strong consistency while maintaining good scalability... Read More

[DB Seminar] Spring 2017: Huanchen Zhang

Speaker:

Huanchen Zhang

Succinct data structures are those that require, asymptotically, only the minimum number of bits required by information theory, while still answering queries efficiently. Despite the importance of space efficiency, particularly for today’s massive-scale data services, succinct data structures remain primarily of theoretical interest outside of a few application areas. Our goal in this paper is to make succinct tries practical... Read More

[DB Seminar] Spring 2017: Round table discussion

We will have a round table discussion. Read More

[DB Seminar] Spring 2017: Wei (David) Dai

Speaker:

Wei (David) Dai

Machine Learning (ML) systems depend on data engineering – the practice of transforming a small set of raw measurements to a large number of features – to substantially increase the accuracy of their results. However, as ML problem grow in both data size (number of instances) and model size (number of dimensions), existing systems that support data engineering have not... Read More

[DB Seminar] Spring 2017: Round table discussion

We will have a round table discussion. Read More

[DB Seminar] Spring 2017: Joy Arulraj

Speaker:

Joy Arulraj

Joy will give a talk on his work.The difference in the performance characteristics of volatile (DRAM) and non-volatile storage devices (HDD/SSDs) influences the design of database management systems. The key assumption has always been that the latter is much slower than the former. This affects all aspects of a DBMS's runtime architecture. But the arrival of new non-volatile memory (NVM)... Read More