papers

Publications (8)

cs.CL2021

Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources

Sicheng Zhao, Yang Xiao, Jiang Guo +5

Sentiment analysis of user-generated reviews or comments on products and services in social networks can help enterprises to analyze the feedback from customers and take correspond…

cs.LG2021

Differentiable NAS Framework and Application to Ads CTR Prediction

Ravi Krishna, Aravind Kalaiah, Bichen Wu +4

Neural architecture search (NAS) methods aim to automatically find the optimal deep neural network (DNN) architecture as measured by a given objective function, typically some comb…

cs.AR2026

Design Conductor 2.0: An agent builds a TurboQuant inference accelerator in 80 hours

The Verkor Team, Ravi Krishna, Suresh Krishna +1

Driven by a rapid co-evolution of both harness and underlying models, LLM agents are improving at a dizzying pace. In our prior work (performed in Dec. 2025), we introduced "Design…

cs.CV2020

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

Sicheng Zhao, Xiangyu Yue, Shanghang Zhang +8

Large-scale labeled training datasets have enabled deep neural networks to excel across a wide range of benchmark vision tasks. However, in many applications, it is prohibitively e…

cs.AR2020

Accelerating Recommender Systems via Hardware "scale-in"

Suresh Krishna, Ravi Krishna

In today's era of "scale-out", this paper makes the case that a specialized hardware architecture based on "scale-in"--placing as many specialized processors as possible along with…

cs.CV2020

Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation

Sicheng Zhao, Xuanbai Chen, Xiangyu Yue +7

Thanks to large-scale labeled training data, deep neural networks (DNNs) have obtained remarkable success in many vision and multimedia tasks. However, because of the presence of d…