A robust preference for cheap-and-easy strategies over reliable strategies when verifying personal memories

People depend on various sources of information when trying to verify their autobiographical memories. Yet recent research shows that people prefer to use cheap-and-easy verification strategies, even when these strategies are not reliable. We examined the robustness of this cheap strategy bias, with scenarios designed to encourage greater emphasis on source reliability. In three experiments, subjects described real (Experiments 1 and 2) or hypothetical (Experiment 3) autobiographical events, and proposed strategies they might use to verify their memories of those events. Subjects also rated the reliability, cost, and the likelihood that they would use each strategy. In line with previous work, we found that the preference for cheap information held when people described how they would verify childhood or recent memories (Experiment 1); personally-important or trivial memories (Experiment 2), and even when the consequences of relying on incorrect information could be significant (Experiment 3). Taken together, our findings fit with an account of source monitoring in which the tendency to trust one’s own autobiographical memories can discourage people from systematically testing or accepting strong disconfirmatory evidence.

Robust tensor analysis with L1-norm

Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based tensor analysis (TPCA-L1), which is robust to outliers. Experimental results upon face and other datasets demonstrate the advantages of the proposed approach. © 2006 IEEE.

Robust H.264/AVC video transmission using data partitioning and unequal loss protection

In this work, we present an adaptive unequal loss protection (ULP) scheme for H264/AVC video transmission over lossy networks. This scheme combines erasure coding, H.264/AVC error resilience techniques and importance measures in video coding. The unequal importance of the video packets is identified in the group of pictures (GOP) and the H.264/AVC data partitioning levels. The presented method can adaptively assign unequal amount of forward error correction (FEC) parity across the video packets according to the network conditions, such as the available network bandwidth, packet loss rate and average packet burst loss length. A near optimal algorithm is developed to deal with the FEC assignment for optimization. The simulation results show that our scheme can effectively utilize network resources such as bandwidth, while improving the quality of the video transmission. In addition, the proposed ULP strategy ensures graceful degradation of the received video quality as the packet loss rate increases. © 2010 IEEE.