Customer-obsessed science
Research areas
-
August 21, 20269 min readExtendable framework enables testing agents on the full set of capabilities required to successfully complete a procedure, not isolated proxy tasks.
-
July 30, 20268 min read
-
-
July 9, 202610 min read
-
Featured news
-
CIKM 20192019Product search is one of the most popular methods for people to discover and purchase products on e-commerce websites. Because personal preferences often have an important influence on the purchase decision of each customer, it is intuitive that personalization should be beneficial for product search engines. While synthetic experiments from previous studies show that purchase histories are useful for identifying
-
EMNLP 20192019Automated fact verification has been progressing owing to advancements in modeling and availability of large datasets. Due to the nature of the task, it is critical to understand the vulnerabilities of these systems against adversarial instances designed to make them predict incorrectly. We introduce two novel scoring metrics, attack potency and system resilience which take into account the correctness
-
EMC+SIPI 20192019Unintended Electromagnetic interference (EMI) is a common occurrence in all consumer electronics, which can often fail compliance margins of FCC and/or CE, when best practices of grounding, shielding and overall system integration are not followed. The measurement of EMI for regulatory compliance has been studied extensively and there are standard test labs which certifies for EMI. However, predicting the
-
ICCV 20192019Recent advances in deep learning greatly boost the performance of object detection. State-of-the-art methods such as Faster-RCNN, FPN and R-FCN have achieved high accuracy in challenging benchmark datasets. However, these methods require fully annotated object bounding boxes for training, which are incredibly hard to scale up due to the high annotation cost. Weakly-supervised methods, on the other hand,
-
GCPR 20192019Dense prediction tasks typically employ encoder-decoder architectures, but the prevalent convolutions in the decoder are not image adaptive and can lead to boundary artifacts. Different generalized convolution operations have been introduced to counteract this. We go beyond these by leveraging guidance data to redefine their inherent notion of proximity. Our proposed network layer builds on the permutohedral
Collaborations
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
View all