activity
20182020
collaborators

6 papers

cs.CL2020

Word2vec Conjecture and A Limitative Result

Falcon Z. Dai

Being inspired by the success of \texttt{word2vec} \citep{mikolov2013distributed} in capturing analogies, we study the conjecture that analogical relations can be represented by ve…

cs.LG2020

Loop Estimator for Discounted Values in Markov Reward Processes

Falcon Z. Dai, Matthew R. Walter

At the working heart of policy iteration algorithms commonly used and studied in the discounted setting of reinforcement learning, the policy evaluation step estimates the value of…

cs.CV2019

DIODE: A Dense Indoor and Outdoor DEpth Dataset

Igor Vasiljevic, Nick Kolkin, Shanyi Zhang +8

We introduce DIODE, a dataset that contains thousands of diverse high resolution color images with accurate, dense, long-range depth measurements. DIODE (Dense Indoor/Outdoor DEpth…

cs.CL2019

Towards Near-imperceptible Steganographic Text

Falcon Z. Dai, Zheng Cai

We show that the imperceptibility of several existing linguistic steganographic systems (Fang et al., 2017; Yang et al., 2018) relies on implicit assumptions on statistical behavio…

cs.LG2019

Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards

Falcon Z. Dai, Matthew R. Walter

We propose a new complexity measure for Markov decision processes (MDPs), the maximum expected hitting cost (MEHC). This measure tightens the closely related notion of diameter [JO…

cs.CL2018

End-to-End Content and Plan Selection for Data-to-Text Generation

Sebastian Gehrmann, Falcon Z. Dai, Henry Elder +1

Learning to generate fluent natural language from structured data with neural networks has become an common approach for NLG. This problem can be challenging when the form of the s…